Tootfinder

A look at the World Cup plans of The Guardian and NYT's The Athletic, including dedicated newsletters, and the single-issue independent magazine Golden Goal (Neel Dhanesha/Nieman Lab)
https://www.niemanlab.org/2026/05/newsl…

Newsletters, live coverage, a one-time magazine: The World Cup is becoming a testbed for journalism experiments
"It's one of those huge, gigantic things that sort of go beyond sports. It's like a life-measurement mechanism."

I spent some more time working on Retort, ran a lot of experiments and tuned the output evaluator to measure what I think is important. Did the LLM implement the full spec? Is there good test coverage and working tests? How long did it take, and how much did it cost? Easy to run your own experiments, and test on your own code, with statistical (ANOVA) modeling of the results.

How reliable, fast and expensive is each version of Claude Code (Sonnet through Opus 4.8-fast)
Every few weeks a new frontier model tops the leaderboards, and the implicit advice is “upgrade.” Sites like llm-stats.com rank models well…

Come join us on August 12th in celebrating a partial solar eclipse and the Perseids meteor shower! Experience shows in a mobile planetarium, hands-on experiments, lectures – and, of course, sky observations.
https://www.mps.mpg.de/lange-nacht-der-astron…

(YouTube) Unboxing your #BCI https://www.youtube.com/watch?v=Moh_ytOHAwU Plug into your living mouse for unspecified animal experiments, by Science Corp.

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 6176 nodes and 178151 edges.
Tags: Biological, Protein interactions, Unweighte…

DNQ: Deep Nash Q-Network for Partially Observable n-Player Games
Qintong Xie, Edward Koh, Xavier Cadet, Peter Chin
https://arxiv.org/abs/2606.06480 https://arxiv.org/pdf/2606.06480 https://arxiv.org/html/2606.06480
arXiv:2606.06480v1 Announce Type: new
Abstract: Many real-world competitive systems require multiple decision-makers to act simultaneously under shared constraints, limited information, and repeated interaction, as in auctions, resource allocation, and security competition. We study multi-turn simultaneous bidding as a controlled testbed for such problems and propose DNQ, a solver-in-the-loop equilibrium supervision framework for training bidding agents. DNQ alternates between trajectory collection, critic-based payoff estimation, equilibrium computation, and policy imitation. At each visited state, a shared critic predicts either pairwise payoff matrices or an exact N-player payoff tensor, an external solver computes equilibrium strategies, and the agents are trained by minimizing the KL divergence between their masked policies and the solver-derived equilibrium targets. We focus on a scalable pairwise formulation that greatly reduces equilibrium-solving cost and training time compared with the exact formulation, while the shared critic amortizes payoff learning across agents and states. Experiments compare the pairwise and exact variants using critic loss, policy entropy, bidding resource usage, and training cost, showing that the pairwise method scales to larger numbers of agents, whereas the exact method becomes computationally impractical as the joint game grows. These results illustrate the trade-off between strategic fidelity and scalability in repeated competitive environments.
toXiv_bot_toot

An interview with Amazon SVP of Devices Panos Panay on designing custom chips for Echo and Fire TV devices, experimenting with AI-enabled gadgets, and more (Arjun Kharpal/CNBC)
https://www.cnbc.com/2026/07/02/amazon-ai-chips-devices.html

Amazon is designing its own AI chips for Echo, Fire TV and future devices, exec tells CNBC
Amazon hardware chief Panos Panay says the company is designing custom chips for key devices as it experiments with AI gadgets.

Replaced article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- In situ magnetic-field stabilization for quantum-gas experiments
Gvozdiovas, Vald\'es-Curiel, Liang, Mercado-Gutierrez, Pi\~neiro, Tao, Trypogeorgos, Zhao, Spielman
…

interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

“American families don’t want experiments with their money,” a voice booms.
“They want jobs, growth, and available credit.
When crypto gets a free pass, communities pay the price.”
The 30-second video, which launched in Washington DC this month,
is part of a six-figure advertising campaign by the Independent Community Bankers of America (ICBA),
meant to help fight a landmark bill that will determine how America’s multibillion-dollar crypto sector is regulated.…

‘Crypto v community’: 4,000 local US lenders join forces to fight ‘stablecoins’ law
Up to 4,000 community banks fear looming legislation to regulate digital cash will deprive rural firms and farmers of $850bn-worth of loans

I have just read someone that thinks that he found a Candidate Theory of Everything and solved the black hole information paradox... by using an AI tool (Claude, but it is irrelevant, to be honest), in 1 week.
If you want to waste your time search for "I Used AI to Produce a Candidate Theory of Everything". But please do not use this to mock the guy.
The overconfidence created by these tools is terrifying.
A related paper, that is not that guy's paper:

AI advice suppresses people's willingness to say "I don't know", even when the advice is wrong and accuracy is incentivized
Knowing when to say "I don't know" is fundamental to human judgment, yet AI assistants offer a fluent answer to almost any question. In five experiments (N = 3,132; four preregistered, one direct replication), participants answered difficult questions and could always decline to respond. We engineered the questions so that AI advice was wrong, separating AI use from its accuracy. Merely having access to AI nearly eliminated participants' willingness to suspend judgment, and this held whether th…

I spent a while trying to work out when Tidal was born, but eventually realised it didn't have a birthday, it slowly emerged and came into focus over an extended, continuous series of experiments, events and collaborations..
However I did my first talk on live coding something like an uzulang written in Haskell on 17th September 2009, so maybe we could pretend that uzu culture turns 17 on 17th Sept 2026?

Replaced article(s) found for physics.comp-ph. https://arxiv.org/list/physics.comp-ph/new
[1/1]:
- Walking on Spheres and Talking to Neighbors: Variance Reduction for Laplace's Equation
Michael Czekanski, Benjamin Faber, Margaret Fairborn, Adelle Wright, David Bindel
https://arxiv.org/abs/2404.17692 https://mastoxiv.page/@arXiv_physicscompph_bot/112358997081867258
- From Experiments to Expertise: Scientific Knowledge Consolidation for AI-Driven Computational Phy...
Haonan Huang
https://arxiv.org/abs/2603.13191 https://mastoxiv.page/@arXiv_physicscompph_bot/116237798566267809
- Grounded autonomous scrutiny at scale: emergent critique from reproduction of published computati...
Haonan Huang
https://arxiv.org/abs/2604.12198 https://mastoxiv.page/@arXiv_physicscompph_bot/116407633668438262
- libwignernj: a reusable C/C /Fortran/Python library for exact Wigner symbols and related coeffic...
Susi Lehtola
https://arxiv.org/abs/2605.06634 https://mastoxiv.page/@arXiv_physicscompph_bot/116537877078468610
- An Overview of Relativistic Particle Pushers and their Extension to Arbitrary Order Accuracy
Holger Schmitz
https://arxiv.org/abs/2603.06509 https://mastoxiv.page/@arXiv_physicsplasmph_bot/116198419420211577
- paces: Parallelized Application of Co-Evolving Subspaces, a method for computing quantum dynamics...
R. Kevin Kessing
https://arxiv.org/abs/2603.07341 https://mastoxiv.page/@arXiv_quantph_bot/116204568573959976
- Topology of Plasma Wakefields Driven by Two Color Laguerre Gaussian Laser Pulses
Saumya Singh, Dinkar Mishra, Shivani Aggarwal, Bhupesh Kumar, Pallavi Jha
https://arxiv.org/abs/2605.18336 https://mastoxiv.page/@arXiv_physicsplasmph_bot/116600306625433164
- Resolved Anderson localization of light in dense three-dimensional dielectric disorder
Yevgen Grynko, Jens F\"orstner
https://arxiv.org/abs/2605.25098 https://mastoxiv.page/@arXiv_physicsoptics_bot/116639935317087700
- A Reproducible Benchmark and Evidence-Retrieval Software Framework for Silicon Detector R&D Liter...
Tianqi Gao, Ruobing Jiang, Dawei Fu, Qiang Li, Matthew Kenzie
https://arxiv.org/abs/2606.24725
- Probing Light-Matter Interaction with Topological Data Analysis
Timothy Holt, Maxim Goryachev, Jeremy Bourhill
https://arxiv.org/abs/2606.30007 https://mastoxiv.page/@arXiv_physicsappph_bot/116837978382710147
toXiv_bot_toot

First experiments on optimizing efficiency / usage of the microscope bench workstation went... Poorly.
The first, grander, idea was to grab a spare SSD, install xcp-ng on it, and use the box as a second VM server with the microscope software running in a guest with USB passthrough to the mouse, keyboard, joystick, camera, and stage.
This would let me push CI jobs to the extra CPU cores when it wasn't busy, as well as live-migrating VMs for critical services to prevent downtim…

Forbes launches The Daily Brief, an AI-powered audio briefing that turns its top three stories of the day into a five-minute podcast, which is checked by humans (Sara Guaglione/Digiday)
https://digiday.com/media/ai-podcast-experiments-march-on-…

AI podcast experiments march on with Forbes’ new daily audio briefing
Forbes bets on AI-generated audio with a five-minute daily news brief. Stories are selected by product, editorial and an internal AI tool.

From collider experiments to large-scale astronomy systems, this session by Dmitriy Kostunin and Julian von Hoerschelmann-Schliwinski takes an honest look at where AI delivers measurable gains, and where it falls short.
Learn more about this session: https://2026.berlinbuzzwords.de/session/ai-in-the-physical-world-from-observation-to-discovery/

Phosphorus-nitrogen systematics of first-generation planetesimals constrain life-essential element delivery to Earth: #life, found in different ratios in asteroidal bodies related to iron meteorites than in younger asteroids.

Invisible walls: how pedestrians navigate around social interactions
https://arxiv.org/abs/2607.20876

Quick Ways to Help Animals Used in Experiments #AnimalRights

Enigma, which runs large-scale experiments exploring how humans interact with robots, emerges from stealth with a $70M seed led by Index Ventures and Ribbit (Marina Temkin/TechCrunch)
https://techcrunch.com/2026/07/27/enigma-ra…

Enigma raises $70M to make controlling a robot as easy as adjusting the volume | TechCrunch
The massive seed round was led by Index Ventures and Ribbit Capital, with participation from Sarah Guo's Conviction Partners.

“The project does not involve field research, laboratory experiments, or resource-intensive physical processes. The project-related activities are primarily computer-based and organizational in nature, and focus on the analysis and testing of data-driven infrastructures. Ecological sustainability aspects are therefore only marginally relevant.”
Well, the environmental impact of academic IT projects is indeed marginal compared to commercial operations, but…
⇢

“The project does not involve field research, laboratory experiments, or resource-intensive physical processes. The project-related activities are primarily computer-based and organizational in nature, and focus on the analysis and testing of data-driven infrastructures. Ecological sustainability aspects are therefore only marginally relevant.”
Well, the environmental impact of academic IT projects is indeed marginal compared to commercial operations, but…
⇢

“The project does not involve field research, laboratory experiments, or resource-intensive physical processes. The project-related activities are primarily computer-based and organizational in nature, and focus on the analysis and testing of data-driven infrastructures. Ecological sustainability aspects are therefore only marginally relevant.”
Well, the environmental impact of academic IT projects is indeed marginal compared to commercial operations, but…
⇢

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 2528 nodes and 3864 edges.
Tags: Biological, Protein interactions, Unweighted

A Simulation Methodology Testbed for Typhoon Sensitivity Analysis: Framework Development and Perturbation-Response Experiments with the Pangu Weather Model
Yuehua Peng, Yuchen Zhang, Qin Huang, Chengzhi Ye, Jingsong Yang
https://arxiv.org/abs/2605.21864 https://arxiv.org/pdf/2605.21864 https://arxiv.org/html/2605.21864
arXiv:2605.21864v1 Announce Type: new
Abstract: Understanding how typhoons respond to localized perturbations in their environmental fields is fundamental to assessing the limits of predictability and exploring the potential for track or intensity intervention. This study develops a dedicated simulation methodology testbed for typhoon sensitivity analysis by integrating the Pangu weather model, a high-precision AI forecasting system, with Proportional-Integral-Derivative (PID) closed-loop techniques. The testbed is constructed with modular functional blocks including a meteorological prediction module, an artificial perturbation input interface, a typhoon quantitative modeling module, and a PID closed-loop test module, implemented via a cross-platform MATLAB/ONNX technical framework. A Single-Input Single-Output (SISO) test system was built, with velocity and thermal perturbations set as the core inputs and typhoon track and intensity as the key output targets, to perform controlled perturbation-response experiments. The experiments reveal the feasible perturbation-response range, the parameter tuning behavior of the PID module, and the energy-scale response characteristics under different perturbation modes, and quantify the input-output coupling relationships of the test system. By constructing this testbed on an operational AI weather forecasting model, this study provides a framework that goes beyond idealized sensitivity studies typically validated only on low-order dynamical models. The testbed offers an expandable platform for investigating typhoon sensitivity to artificial environmental perturbations and provides a foundation for subsequent expansion toward multi-input multi-output architectures and advanced analysis strategies such as nonlinear PID or model predictive control.
toXiv_bot_toot

7 requests later, I got the data of a full day. 186 kWh in total. The chart is nice for the bot. More interesting is the raw data do do all kinds of experiments. For example calculating how various battery sizes would change self consumption.
Time to get to sleep.

Part of important experiments with 'types of data governance that establish a global knowledge commons, while supporting local communities'
How Open Licensing is Changing with AI: The NOODL License https://community.mozilladatacollectiv

How Open Licensing is Changing with AI: The NOODL License
Author: Alek Tarkowski For the last twenty five years, standardized open licenses were increasingly seen as a main tool for democratizing access to knowledge. Over less then a decade, a relatively narrow set of canonical choices emerged: the Creative Commons licensing stack https://creativecommons.org/licenses/list.en, coupled with

Scientists finally figured out how homing pigeons navigate on cloudy days. Macrophages in the liver!
https://www.youtube.com/watch?v=2n1qqC7QfdE&feature=youtu.be
(The video explains how the experiments worked. The author/narrator has a funky voice--but all…

We introduce Robin,
the first multi-agent system capable of fully automating both hypothesis generation and data analysis for experimental biology.
By integrating literature search agents with data analysis agents,
Robin can generate hypotheses,
propose experiments,
interpret experimental results,
and generate updated hypotheses,
achieving a semi-autonomous approach to scientific discovery.
By applying this system, we were able to identify pr…

another album of lost #eno songs, along with the pre-"another green world" demos. https://www.moredarkthanshark.org/eno_int_blitz-nov83.html

AI advice suppresses people’s willingness to say “I don’t know”, even when the advice is wrong and accuracy is incentivized.
https://arxiv.org/abs/2607.13562v1

AI advice suppresses people's willingness to say "I don't know", even when the advice is wrong and accuracy is incentivized
Knowing when to say "I don't know" is fundamental to human judgment, yet AI assistants offer a fluent answer to almost any question. In five experiments (N = 3,132; four preregistered, one direct replication), participants answered difficult questions and could always decline to respond. We engineered the questions so that AI advice was wrong, separating AI use from its accuracy. Merely having access to AI nearly eliminated participants' willingness to suspend judgment, and this held whether th…

🔊 #NowPlaying on #BBCRadio3:
#LateJunction
- Medieval psych rock and hellhounds on the loose
Jennifer Lucy Allan presents adventurous explorations in sound, from Tashi Dorji’s new guitar experiments to a local fable reimagined by a children’s improvising orchestra.
Relisten now 👇
https://www.bbc.co.uk/programmes/m002x54b

Relaxation of Incommensurate Structures via Quantum Models
Mengfan Tu, Huajie Chen, Daniel Massatt
https://arxiv.org/abs/2606.31104 https://arxiv.org/pdf/2606.31104 https://arxiv.org/html/2606.31104
arXiv:2606.31104v1 Announce Type: new
Abstract: Accurately modeling structural relaxation in incommensurate systems is intrinsically challenging due to the absence of global translational symmetry. In this work, we develop a variational quantum framework for structural relaxation in incommensurate Schr\"{o}dinger models, where displacement fields are formulated on the configuration space and the electronic Hamiltonian is represented in reciprocal space. This yields well-defined relaxed energy, local density of states, and forces through thermodynamic limits. We propose an anisotropic scattering-channel approximation, and prove exponential convergence of the approximate equilibria. Numerical experiments are performed to support the analysis and show that the model captures domain-wall formation and its impact on the electronic spectrum.
toXiv_bot_toot

Ich habe es wieder getan. 🤡
Es ist Release-Day von WordPress 7.0 und was macht mein Gehirn? „Komm schon, klick auf Update. Was soll schon schiefgehen? Du brauchst kein Staging, du lebst am Limit!“
Das Ergebnis des heutigen Wahnsinns-Experiments: Das Blog steht noch! Also… das meiste davon. Sagen wir mal so: Die Startseite atmet, drei Plugins weinen leise im Hintergrund und das Theme hat leichte Identitätsprobleme.

Kennt ihr InsideAI auf Youtube? #KI

InsideAI
Made by humans, for humans. Inside AI features leading safety research, social experiments, custom models and robotics!

The Date of #Eilmer of Malmesbury’s Flight: https://academic.oup.com/nq/advance-article/doi/10.1093/notesj/gjag066/8671576 (about a guy allegedly doing gliding flight experiments - and observing Halley's comet - a millennium ago) -> Did a medieval flying monk spot Halley’s comet, twice? It’s complicated: https://arstechnica.com/science/2026/06/did-a-medieval-flying-monk-spot-halleys-comet-twice-its-complicated/ - yeah, right, because the sources are ... tenuous at best.

Adaptive Beam Selection for Efficient Scanning Probe Tomography
San Dinh, Zichao Wendy Di, Matt Menickelly
https://arxiv.org/abs/2606.21713 https://arxiv.org/pdf/2606.21713 https://arxiv.org/html/2606.21713
arXiv:2606.21713v1 Announce Type: new
Abstract: In X-ray tomography, reconstruction quality generally improves with larger numbers of projections. However, more projections increase experiment costs, acquisition time and the radiation dose imparted to the sample. One mitigation to these trade-offs is to adopt a sequential design of experiments, in which each subsequent measurement is determined as a function of previously acquired data in order to maximize information gain. In practice, a widely used heuristic to maximize information is to align beams with the edges of the sample. A key challenge, however, is that the true sample is unknown, so identifying edge-aligned beams typically requires reconstructing the sample based on available measurements. This work proposes a novel sequential design method that identifies edge-aligned measurements directly from the sinogram, bypassing any reconstruction, thereby improving computational efficiency and reducing the experimental design's susceptibility to reconstruction errors. Our method dynamically selects the next set of measurement beams by maximizing an acquisition function that balances exploration and exploitation over the domain of all possible measurements, improving reconstruction quality while reducing measurement redundancy.
toXiv_bot_toot

GPE: Evaluating Robust Evidence Aggregation for Fact Verification under Controllable GEO-Style Poisoning
Zhaoqi Wang, Zijian Zhang, Xiaomei Yuan, Pengtao Kou, Jiamou Liu, Zhen Li, Liehuang Zhu
https://arxiv.org/abs/2607.20730 https://arxiv.org/pdf/2607.20730 https://arxiv.org/html/2607.20730
arXiv:2607.20730v1 Announce Type: new
Abstract: Large language models increasingly use search tools to retrieve up-to-date information, introducing a new attack surface in which retrieved documents can be manipulated. This risk is amplified by the development of generative engine optimization, which can make selected content more likely to be retrieved, cited, and adopted by models. Existing fact-verification benchmarks and evaluation frameworks do not provide the controlled evidence environments needed to assess robustness against GEO poisoning. We therefore propose GPE, which consists of a multi-domain fact-verification benchmark and an evaluation framework for controlling evidence sources and poisoning ratios. Experiments across multiple verification methods and poisoning attacks demonstrate that GPE exposes robustness degradation and efficiency trade-offs that cannot be observed through clean evaluation alone, confirming the need to evaluate fact verification under adversarial evidence environments.
toXiv_bot_toot

Experiments with interacting ultracold polar molecules
Philip D. Gregory, Jonathan M. Mortlock, Daniel K. Ruttley, Simon L. Cornish
https://arxiv.org/abs/2607.25519 https://

The Butterfly Defect Effect in Cylindrical Shell Buckling: Non-localized Interactions of Localized Imperfections
Uba K. Ubamanyu, Antoine Blond, John W. Hutchinson, Pedro M. Reis
https://arxiv.org/abs/2607.19245 https://arxiv.org/pdf/2607.19245 https://arxiv.org/html/2607.19245
arXiv:2607.19245v1 Announce Type: new
Abstract: We investigate the buckling of axially compressed cylindrical shells containing localized defects, focusing on interactions among multiple defects and between them and the shell edges. Using high-fidelity finite-element simulations, we first characterize the parameter space of single-dimple sensitivity, defect-edge coupling, and pairwise defect-defect interactions. Building on this deterministic baseline, we run stochastic simulations of shells with randomly distributed imperfections whose amplitudes are sampled from a log-normal distribution. Post-buckling deformations form non-axisymmetric, butterfly-shaped patterns whose `wings' reach far across the shell surface. This spatial extent induces unavoidable interactions with neighboring defects and the clamped edges, so that buckling is not necessarily initiated by the deepest defect. A larger defect population raises the likelihood of an extreme defect, producing a statistical size effect: as the mean number of defects grows, the mean knockdown factor decreases asymptotically and its variability decays exponentially. The butterfly defect effect qualitatively explains the scatter in historical experimental data by correlating the knockdown factor with the cylinder length-to-thickness ratio ($H/t$) rather than the radius-to-thickness ratio ($R/t$) alone, thereby establishing $H$ as a key parameter for stability alongside $R$ and $t$. Nonetheless, the knockdown factors obtained here remain well above those reported in historical experiments, indicating that the localized Gaussian dimple, though nearly the worst-case imperfection for spherical shells, is not so for cylinders.
toXiv_bot_toot

interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

One of the great things about the Lyon Algorave was the huge diversity of live coding languages and systems being used, all kinds of strange experiments making weird noises.. with hundreds of ravers dancing to them

Theoretical development of an operational wave-induced ice erosion model through laboratory experiments
Wenjun Lu, Behnam Ghadimi, Dominique Mouaze, Marianne Font, R\'emi Lambert, Harvey Goodwin, Widar Weizhi Wang, Raed Lubbad, Sveinung L{\o}set
https://arxiv.org/abs/2607.20118 https://arxiv.org/pdf/2607.20118 https://arxiv.org/html/2607.20118
arXiv:2607.20118v1 Announce Type: new
Abstract: Wave-induced melting of vertical ice fronts is represented in several operational iceberg and coastal-erosion models by the rough-wall parameterization of White (1980), whose closure chain is incompletely documented and whose commonly used compact expression is stated at the waterline. We reconstruct the formulation, specify the rough-turbulent wave-friction closure using Jonsson's implicit relation and its Lambert-W solution, and extend the model to a depth-resolved melt-rate profile under linear wave kinematics. Because the horizontal and vertical orbital-velocity components are linked, we use the horizontal component as a convenient representative scale and introduce a dimensionless coefficient alpha for the remaining closure uncertainty. The reconstruction gives a waterline coefficient of 3.0 x 10^-4 with White's resultant-velocity definition and 2.09 x 10^-4 for the reference choice alpha = 1; neither reproduces White's published 1.46 x 10^-4 directly. Two monochromatic wave-flume experiments with freshwater ice are then used to calibrate alpha from profiles below the wave trough. The full Lambert-W friction coefficient is used in this calibration. Best-fit values are 0.684 and 0.612 for periods of 1.54 and 0.87 s, respectively, a relative difference of approximately 11%. Their corresponding effective waterline coefficients, 1.43 x 10^-4 and 1.28 x 10^-4, are close to White's published value but do not constitute an independent validation. The fitted profiles reproduce the observed depth dependence below the trough, while deviations near the surface expose unresolved effects of intermittent submergence, local wave impact, and uncertain thermal forcing.
toXiv_bot_toot

Here's a couple thought experiments:
Would you allow an AI company to make a model trained off your open source licensed work, if the model was guaranteed to be open weights under an MIT-like license, and the training dataset was public?
And
Do you think that the existing licenses of open source work allow this already? (answers may vary by license)

PS.
Here are the two outlets. This is probably not how it will look in the end, but just a starting point. Once I have the water flowing how I want it to, I will use pond foam sealant to lock the rocks into place and force the water into its final channels and patterns but as you can imagine there is some trial and error to be done before that big step.
For noe you can see there is a fold of liner sitting vertically betwewn the rocks to split the channel. I really have no idea where the water will get to once at full force so this might be too high, or too low but it should not be too far off.
The main thing is that the water is contained within the greater system around the tree. That's the trickiest part right now.
It is a wonderful tree. We don't want to drown it.
Speaking of which, if you are wondering about water. Yes. This is thousands of litres of water. But at this point I am not worried if I need to fill up and drain the bog filter a few times. All extracted water will go into the rest of the garden anyway, so aside from a little evaporation, nothing will be wasted.
Still waiting on it to fill. Looks like it won't be full before quitting time. oh well! Back tomorrow water experiments!
#pandemicpond #PoolPond #gardening #portalberni #home #yard #bloomscrolling #BackyardProject

interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

Ultrametric Graphons and Hierarchical Community Networks: Spectral Theory and Applications
\'Angel Alfredo Mor\'an Ledezma
https://arxiv.org/abs/2605.13423 https://arxiv.org/pdf/2605.13423 https://arxiv.org/html/2605.13423
arXiv:2605.13423v1 Announce Type: new
Abstract: We develop a theory of ultrametric graphons as limiting objects for random networks with nested hierarchical community structure. A graphon $W:[0,1]^2\to[0,1]$ is called ultrametric if $W(x,y)=w(d(x,y))$, where $d$ is an ultrametric on $[0,1]$ induced by a family of nested partitions and $w$ is a positive kernel. The resulting random graphs exhibit a nested hierarchical community structure in which the density of connections is governed by the ultrametric distance between vertices. The Laplacian $L_d^k$ of the deterministic graph sampled from an ultrametric graphon is itself an ultrametric Laplacian, whose eigenvalues and spectral projectors admit completely explicit closed-form expressions in terms of the community sizes and inter-community connection densities. We show that the normalized eigenvalues and spectral projectors of the random Laplacian $L_r^k$ are arbitrarily close to those of $L_d^k$ with high probability as $k\to\infty$, so that the explicit formulas for $L_d^k$ provide closed-form approximations for the spectrum and spectral projectors of $L_r^k$. As applications: a sign structure theorem generalizes the Fiedler vector criterion to hierarchical networks with arbitrarily many communities; a detectability threshold $p^*=\min_i\rho_i$ governs spectral community detection for one-level hierarchical graphons; the pseudo-inverse Laplacian $L_W^ $ is constructed and shown to be the almost sure limit of the pseudo-inverse of $L_r^k$, implying that hitting and commute times collapse to quantities depending only on the expected degrees of the endpoints; and explicit closed-form stability conditions for the SIS disease-free equilibrium reveal a fundamental tension between homogeneous and heterogeneous community structures, confirmed by numerical experiments.
toXiv_bot_toot

Volador 1.0: A Data-Driven Air-Sea Full-Coupling Regional Forecast Model with Submesoscale-Permitting Based on MOE-Swin-Transformer Framework
Yuhang Zhu, Jianxin Wang, Yu-kun Qian, Yineng Li, Yahui Liu, Yankun Gong, Shilin Tang, Shiqiu Peng, Tao Song
https://arxiv.org/abs/2605.24032 https://arxiv.org/pdf/2605.24032 https://arxiv.org/html/2605.24032
arXiv:2605.24032v1 Announce Type: new
Abstract: A data-driven air-sea full-coupling regional forecast model with submesoscale-permitting, named "Volador 1.0", is developed for the South China Sea (SCS). The model features a Swin-Transformer framework integrated with a Mixture-of-Experts (MoE) system, a latent space interaction architecture based on Cross-Grid Bidirectional Cross-Attention, and a fast-slow dual-branch architecture. Both the three-month hindcast test and the 15-day operational real-time forecasting demonstrate that Volador 1.0 has a very encouraging and promising performance in 0-72h forecasting of temperature and salinity in the 0-500m upper ocean as well as the sea surface height with root-mean-square-error (RMSE) or mean absolute error (MAE) smaller than or at least comparable to those from the reanalysis datasets REDOS V2.0 and GLORYS12 and the state-of-the-art regional numerical model Regional Ocean Modeling System (ROMS). In particular, Volador 1.0 demonstrates its capability of capturing/forecasting submesoscale processes including internal waves, with an energy spectrum well representing sub- to mesoscale energy cascade as expected by the classical turbulence theory. Further analysis based on ablation experiments shows that the air-sea full-coupling framework, which takes into account the dynamic exchanges of momentum and heat fluxes between the atmosphere and the ocean, indeed helps improve the model's performance compared to the non-full-coupling one. Volador 1.0, though still subject to refinement in the coming future with a large space for improvement, blazes a path for an accurate, fine and fast marine environment forecasting, and thus could help promote our capability of disaster prevention and mitigation in the SCS as well as in other coastal regions where these innovative techniques can be applied.
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STCC: A Unified Source-Channel Semantic Token Coding Framework for Semantic Communications
Zhicheng Bao, Chen Dong, Sen Wang, Long Liu, Nan Ma, Hao Chen, Xiaodong Xu, Yinqiu Liu, Ping Zhang
https://arxiv.org/abs/2606.11819 https://arxiv.org/pdf/2606.11819 https://arxiv.org/html/2606.11819
arXiv:2606.11819v1 Announce Type: new
Abstract: Deep Joint Source-Channel Coding (JSCC) has emerged as a promising paradigm for overcoming the ``cliff effect" in wireless communications. However, existing Deep JSCC frameworks operate directly on raw analog data such as image pixels rather than the discrete semantic tokens that foundation models require. Moreover, traditional systems employ fixed, hand-designed constellations that treat all tokens equally, leading to catastrophic random errors under channel noise. In this paper, the Semantic Token Codebook Communication (STCC) is proposed as a unified source-channel semantic token coding framework designed to transmit the discrete semantic tokens of foundation models over noisy channels. The core of STCC is the Semantic Token Codec (STC). It accepts discrete tokens as input, which maintains compatibility with foundation models while employing a residual multiple layer perceptron, i.e., MLP-based encoder that learns geometrically structured constellations optimized with a triple-loss objective. This learned mapping forces the channel topology to align with the semantic embedding space, ensuring that channel noise results in topological errors rather than random corruption. This phenomenon is theoretically and empirically characterized, identifying ``Semantic Drift" in symbolic modalities and ``Structural Distortion" in perceptual modalities, where errors shift predictions to semantically or structurally similar tokens. Extensive experiments demonstrate that STCC significantly outperforms traditional systems in low-SNR regimes, effectively converting channel noise into semantic variations without requiring receiver-side modification.
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PhantomSeal: Proactive Deepfakes Defense with Identity/Context Protection and Forensic Tracing
Liangqin Ren, Zeyan Liu, Ye Wang, Yuxin Chen, Fengjun Li, Bo Luo
https://arxiv.org/abs/2607.20564 https://arxiv.org/pdf/2607.20564 https://arxiv.org/html/2607.20564
arXiv:2607.20564v1 Announce Type: new
Abstract: Deepfakes, especially face-swapping attacks, pose significant challenges to authenticity, security, and ethics across science, engineering, and society. While most existing detection/tracing approaches operate post hoc, proactive defenses that aim to intervene before deepfake generation remain limited in terms of real-world effectiveness. In this paper, we present PhantomSeal, the first proactive defense to simultaneously protect both the identity and the context of users' images from being used in face-swapping attacks, while supporting forensic tracing. We present a novel cloaking technique that embeds a selected identity as a stealthy identifier. This mechanism steers the deepfake generation process toward producing content that resembles the chosen cloak identity, thereby preventing successful face-swapping while enabling effective feature-based forensic analysis. The effectiveness and robustness of PhantomSeal is demonstrated in extensive experiments across different face-swapping architectures and models. For example, it reduces the attack success rate of SimSwap, an advanced deepfake model, to 0.30%, and correctly identifies 97.97% of manipulated content. Codes can be found at https://github.com/LiangqinRen/PhantomSeal
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ANNS-AMP: Accelerating Approximate Nearest Neighbor Search via Adaptive Mixed-Precision Computing
Mingkai Chen, Cheng Liu, Shengwen Liang, Lei Zhang, Xiaowei Li, Huawei Li
https://arxiv.org/abs/2606.07156 https://arxiv.org/pdf/2606.07156 https://arxiv.org/html/2606.07156
arXiv:2606.07156v1 Announce Type: new
Abstract: Approximate nearest neighbor search(ANNS) is a critical kernel in modern applications such as LLM and recommendation systems.However,its efficiency is fundamentally limited by the need to compute distances between a query and a massive number of high-dimensional vectors,most of which are non-neighbors.Existing approaches reduce redundancy via index optimization or early termination,but remain constrained by fixed-precision computation,leading to unnecessary arithmetic and memory bandwidth overhead.This paper presents ANNS-AMP,an adaptive mixed-precision framework and accelerator that adapts the precision of distance computation to the characteristics of queries and data distribution.The key insight is that different regions of the vector space require different levels of precision to preserve top-k accuracy.ANNS-AMP leverages the clustered structure of PQ-based indices and introduces a lightweight predictor to determine cluster-level precision at runtime based on features such as scale,radius,and query distance.To efficiently realize variable-precision execution,we design a bit-serial accelerator with a bit-interleaved data layout,enabling throughput to scale with reduced precision while mitigating memory bandwidth bottlenecks and load imbalance through a greedy scheduling strategy.Moreover,the runtime predictor can also reuse the bit-serial computing array for efficient runtime prediction and can be fitted to the ANNS pipeline without performance penalty.According to our experiments on representative datasets,ANNS-AMP achieves 163.76x,10.57x,and 2.06x performance speedups on average,and reduces average energy consumption by 1100.00x,39.41x,and 6.66x compared to CPU,GPU,and customized ANNS accelerator baselines,respectively,while maintaining accuracy loss below 2.7%.These results demonstrate that adaptive mixed-precision computing is a promising direction for efficient large-scale ANNS.
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celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 431 nodes and 438 edges.
Tags: Biological, Protein interactions, Unweighted

Wrt to Codeberg kicking out slop:
“How may the compulsive programmer be distinguished from a merely dedicated, hard-working professional programmer? First, by the fact that the ordinary professional programmer addresses himself to the problem to be solved, whereas the compulsive programmer sees the problem mainly as an opportunity to interact with the computer.
The ordinary computer programmer will usually discuss both his substantive and his technical programming problem with others. He will generally do lengthy preparatory work, [...] He develops his program slowly and systematically. When something doesn't work, he may spend considerable time away from the computer, framing careful hypotheses to account for the malfunction and designing crucial experiments to test them.
[...]
When he has finally composed the program he set out to produce, he is able to complete a sensible description of it and to turn his attention to other things.
The professional regards programming as a means toward an end, not as an end in itself. His satisfaction comes from having solved a substantive problem, not from having bent a computer to his.”
—Joseph Weizenbaum, Computer Power and Human Reason, 1976

interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

Chunkwise Aligners for Streaming Speech Recognition
Wen Shen Teo, Takafumi Moriya, Masato Mimura
https://arxiv.org/abs/2605.11422 https://arxiv.org/pdf/2605.11422 https://arxiv.org/html/2605.11422
arXiv:2605.11422v1 Announce Type: new
Abstract: We propose the Chunkwise Aligner, a novel architecture for streaming automatic speech recognition (ASR). While the Transducer is the standard model for streaming ASR, its training is costly due to the need to compute all possible audio-label alignments. The recently introduced Aligner reduces this cost by discarding explicit alignments, but this modification makes it unsuitable for streaming. Our approach overcomes this limitation by dividing the audio into chunks and aligning each label to the leftmost frames of its chunk, whereas transitions between chunks are managed by a learned end-of-chunk probability. Experiments show that the Chunkwise Aligner not only matches the Transducer's accuracy in both offline and streaming scenarios, but also offers superior training and decoding efficiencies.
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Designing single-layer PDMS devices for micron to millimeter-scale deformations
Leon Valentin Gebhard, Alexandre S. Avaro, Gabriel Amselem, Charles N. Baroud
https://arxiv.org/abs/2605.17402 https://arxiv.org/pdf/2605.17402 https://arxiv.org/html/2605.17402
arXiv:2605.17402v1 Announce Type: new
Abstract: The elasticity of PDMS has played a central role in advancing important microfluidic technologies, ranging from early valves to sophisticated organ-on-a-chip systems. However, most deformable microfluidic devices are based on geometries that require complex multi-layer PDMS architectures and include thin membranes, leading to difficult microfabrication and poor stability. Recently, Jain, Belkadi et al. (Biofabrication 16.3 (2024): 035010) introduced a single-layer device in which a wide and long microfluidic channel was deformed by controlling the pressure in two independent and adjacent air chambers. While they demonstrated the ability to deform the channel ceiling to compress biological materials, the design parameters remain unexplored. Here, we perform a numerical study on 14,336 variants of this device and identify the height of the PDMS layer, the width of the microchannel and the width of the air chamber as the main features that determine the ceiling deformation. Three deformation modes are observed as the geometrical parameters are varied: A U shape with a central minimum, a W shape with two minima and a central maximum, or an inverse U shape with an upward-bulging single maximum. The numerical results are validated in experiments that reproduce the three shapes for the predicted geometries and demonstrate vertical ceiling deformations ranging from a few microns to the millimeter scale. The generality of this approach is demonstrated for two example applications: A fully closing single-layer microfluidic valve and an optical lens of controllable anisotropy. This work leverages the rapid prototyping enabled by 3D printing or micro-milling to open new perspectives in microfluidic actuation.
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A Simulation Methodology Testbed for Typhoon Sensitivity Analysis: Framework Development and Perturbation-Response Experiments with the Pangu Weather Model
Yuehua Peng, Yuchen Zhang, Qin Huang, Chengzhi Ye, Jingsong Yang
https://arxiv.org/abs/2605.21864

LowPowAR: Power-Constrained Tone Mapping for Augmented Reality
Weikai Lin, Sheng Zhao, Ian Ross, Carl Marshall, Sushant Kondguli, Yuhao Zhu
https://arxiv.org/abs/2607.19509 https://arxiv.org/pdf/2607.19509 https://arxiv.org/html/2607.19509
arXiv:2607.19509v1 Announce Type: new
Abstract: Everyday-wearable Augmented Reality (AR) glasses must meet strict power limits, making displays a key target for optimization. We cast display power optimization as a power-constrained tone-mapping problem and propose a human-vision-grounded, learning-based framework that maximizes perceptual quality under a given power budget. We introduce an optimization-friendly tone-mapping operator (TMO) parameterization along with a progressive optimization strategy to effectively navigate the quality-vs-power landscape. We distill the iterative optimization into a lightweight feed-forward neural network for real-time deployment. Subjective experiments show that our method yields better perceptual quality than prior work at the same power budget. Project page: https://horizon-lab.org/lowpowar/.
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Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing
Sadegh Majidi, Niloofar Mireshghallah, Kazem Taram
https://arxiv.org/abs/2607.20723 https://arxiv.org/pdf/2607.20723 https://arxiv.org/html/2607.20723
arXiv:2607.20723v1 Announce Type: new
Abstract: This work presents LeakyLMs, a set of attacks that leak proprietary model, architecture, and deployment information from production language models. LeakyLMs is the first to demonstrate that key model and deployment details can be inferred using only token generation timing, even when interacting through remote APIs. LeakyLMs introduces two core attacks. The first attack targets inference optimizations and deployment strategies. For example, our attack detects whether a provider uses speculative decoding, a widely deployed inference-time optimization, and further identifies the context length of the draft model used in the pipeline. Our measurements show that Google Gemini Flash 2.5 uses speculative decoding with a draft context window of approximately 128K tokens. The second attack recovers key architectural properties, including the number of transformer layers, hidden dimension size, and number of attention heads. To achieve this, LeakyLMs builds a detailed and accurate model of token-generation timing on modern NVIDIA GPUs, characterizing how latency scales with model configuration and hardware parameters. The attack then performs a search over the architecture space using this timing model. In experiments with Llama models, the near-correct architectural configuration appears in the top-10 guesses more than 90% of the time.
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interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

Weakly Non-Negative Supermartingales for Omega-Regular Verification
Toru Takisaka, Hongjie Qing, Libo Zhang
https://arxiv.org/abs/2607.17798 https://arxiv.org/pdf/2607.17798 https://arxiv.org/html/2607.17798
arXiv:2607.17798v1 Announce Type: new
Abstract: Martingale-based methods are central to probabilistic program verification, but strong global non-negativity requirements can exclude simple certificates from tractable template classes. Relaxing this requirement enlarges the search space for automated synthesis, but naive relaxations are unsound in the probabilistic setting. We introduce lazy Streett supermartingales and their lexicographic extension, showing that weak non-negativity can nevertheless be used soundly to certify almost-sure satisfaction of $\omega$-regular properties with polynomial templates under a broad class of sampling distributions, including all bounded-support distributions. This extends prior weakly non-negative methods from termination to general $\omega$-regular verification. We further give a compositional account of lexicographic certificates in terms of one-dimensional ones. Experiments on 170 polynomial probabilistic-program benchmarks show increases of 20.0-23.5 percentage points in verification success over the strongly non-negative baseline.
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Emergent topological structure in spontaneous brain-organoid activity
Eve Bodnia, Margaux Basart, Sofie Hai, Lenzie Ford, Nina Miolane, Kenneth S. Kosik, Dirk Bouwmeester, Lincoln D. Carr
https://arxiv.org/abs/2607.16517 https://arxiv.org/pdf/2607.16517 https://arxiv.org/html/2607.16517
arXiv:2607.16517v1 Announce Type: new
Abstract: Neural activity is widely held to organize on low-dimensional structure embedded in a high-dimensional state space. Persistent homology reads such structure directly from the pattern of pairwise correlations, without assuming in advance which variables are relevant. We apply persistent homology to microelectrode-array (MEA) recordings of spontaneous activity from human (Lancaster) and mouse (Pa\c{s}ca) cortical organoids, spanning $26$--$234$ simultaneously sorted units, and ask whether topological data analysis resolves structure at the node counts that neural recordings actually deliver. Building weighted networks in correlation space and characterizing them by Vietoris--Rips filtration, we find that the first homology ($H_1$, loops) rises significantly above a rate- and population-preserving null in $14$ of $18$ datasets. This loop structure occupies a non-redundant core: it is robust to random removal of units yet disrupted by targeted removal of the units that carry it. Topological richness grows with network size, and second homology ($H_2$) emerges significantly above the null only in the larger networks. These results show that persistent homology resolves structured topology in neural recordings at the scale experiments actually deliver.
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Deepfake News Detection: A Multimodal Framework Integrating LipNet, DeepSpeech and ResNET for Enhanced Audio-Visual Analysis
Ameena Khan, Muhammad Ahsan Aziz, Muhammad Junaid Asif, Naeem Akhter, Rana Fayyaz Ahmad
https://arxiv.org/abs/2607.20579 https://arxiv.org/pdf/2607.20579 https://arxiv.org/html/2607.20579
arXiv:2607.20579v1 Announce Type: new
Abstract: Deepfake news refers to AI-generated (or AI ma-nipulated) multimedia content intentionally generated to deceive audiences by manipulating the facial expressions, or speech while maintaining the realistic appearance. The rapid progress of generative AI has made the synthesis of highly realistic fake videos and cloned voices widely accessible, posing a serious threat to the authenticity of digital news media. This paper presents a multi-modal framework that discerns the authenticity of video content by jointly exploiting audio and visual cues, thereby addressing the challenge of detecting the deepfake videos. We proposed a framework that involves features extraction from lip movements, audio content and video frames. Lip movements and speech content are encoded using the LipNet and DeepSpeech2 models, while facial features are extracted by leveraging the use of BlazeFace and represented with ResNet18. The extracted feature vectors are concatenated into a holistic video representation and classified with an ensemble of machine learning and deep learning models, including Random Forest (RF), Multi-layer Perceptron (MLP) and Long Short-Term Memory (LSTM) networks. Exten-sive experiments performed on the FakeAVCeleb dataset shows that the proposed approach attains an accuracy of 94% using augmented audio features, outperforming a state-of-the-art multi-modal ensemble baseline. The results confirm the robustness and practical potential of the proposed framework for deepfake news detection.
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interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

Sidewall effects on the onset of interfacial Holmboe waves in stratified exchange flows at high Schmidt number
Guilherme Siqueira de Aquino, Metten M. de Lange, Adrien Lefauve, Matias Duran-Matute
https://arxiv.org/abs/2607.19565 https://arxiv.org/pdf/2607.19565 https://arxiv.org/html/2607.19565
arXiv:2607.19565v1 Announce Type: new
Abstract: Predicting the onset of interfacial instabilities is central to understanding turbulent mixing in natural and engineered stratified shear flows. Here, we study the onset of travelling Holmboe waves in confined exchange flows along a slope. Earlier stratified inclined duct experiments have mapped this transition, and stability analyses based on measured or prescribed profiles have explained their emergence. However, a predictive criterion linking forcing, geometry, base flow, and wave onset was still lacking. We closed this gap with a long-duct, sharp-interface asymptotic theory for the three-dimensional laminar exchange flow, including the effects of sidewall friction. The resulting analytical solution naturally identifies a confinement-adjusted Froude number, $Fr^*$, which unifies the effects of forcing and confinement into a single measure of the effective laminar exchange flow. Using this solution to parameterise sidewall drag in a practical width-averaged model, we perform linear stability analyses and numerical simulations at high Schmidt number. Together, linear stability analysis, direct numerical simulations, and existing experiments across a range of duct widths show that wave onset is accurately predicted by an approximately constant critical value of $Fr^*$. Deviations arise only in very narrow ducts, where sidewalls influence instability not only by modifying the laminar exchange flow but also by directly damping perturbations and delaying wave onset. These findings provide a predictive criterion for wave onset, reconcile long-standing discrepancies among experimental configurations, and establish lateral confinement as a fundamental control on the transition from laminar exchange to wave-driven mixing in stratified shear flows.
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interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

Which Model Is Actually Serving You? IRIS: Budgeted Black-Box Auditing of Model Substitution and Routing Dilution in LLM Gateways
Yuewei Zhang, Zhi-Hai Zhang, Hanzhang Qin
https://arxiv.org/abs/2607.20860 https://arxiv.org/pdf/2607.20860 https://arxiv.org/html/2607.20860
arXiv:2607.20860v1 Announce Type: new
Abstract: Commercial LLM gateways mediate access to hosted models, but the served backend may not match the advertised one: it may substitute a cheaper model on every request or route only a fraction $\epsilon$ of requests to it. Prior black-box auditors often need a privileged signal (log-probabilities, token ranks, or reference samples) or a target-specific probe, fix the query budget in advance, and return a yes/no verdict. We present $\mathrm{IRIS}$, an audit that needs only the returned text: it asks endpoints to generate random numbers or strings, fingerprints the backend, and is the first to combine, in one text-only audit, detection of whole-stream substitution and fractional dilution, attribution of the served backend, routing-fraction ($\epsilon$) estimation, and a query budget it sizes itself. A cheap pilot fits the exponential query-error decay and freezes that budget before any suspect query is issued. On an intra-family Qwen3 ladder $\mathrm{IRIS}$ verifies the backend at $0.99$ AUROC and sharpens attribution as queries accumulate; across a commercial OpenRouter library it catches $\epsilon{=}0.3$ dilution on margin-qualified pairs at $0.85$ mean power ($0.017$ false-positive rate) and recovers $\epsilon$ to within $0.04$ for enrolled diluents; and a live cross-provider audit flags $14$ of $15$ same-model provider pairs by genuine quantization and kernel deviations, corroborated on third-party MET traces. Against comparable black-box auditors, $\mathrm{IRIS}$ matches or beats detection on shared tasks, and adaptive allocation lifts the matched-budget target-hit rate from $73$% to $87$%. Further experiments cover adversarial gateways, knob identifiability, unseen diluents, and false-positive control.
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celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 2724 nodes and 14322 edges.
Tags: Biological, Protein interactions, Unweighted…

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 912 nodes and 22738 edges.
Tags: Biological, Protein interactions, Unweighted

Atomic oven with rapid thermal response for atom experiments
Weilong Huang, Congjun Zou, Feiyu Dong, Huirong Xiao, Zejian Ren, Shanchao Zhang
https://arxiv.org/abs/2607.04393 ht…

Reducing Linguistic Hallucination in LM-Based Speech Enhancement via Noise-Invariant Acoustic-Semantic Distillation
Zheng Wang, Xiaobin Rong, Hang Su, Tianyi Tan, Junnan Wu, Lichun Fan, Zhenbo Luo, Jian Luan, Jing Lu
https://arxiv.org/abs/2605.08608 https://arxiv.org/pdf/2605.08608 https://arxiv.org/html/2605.08608
arXiv:2605.08608v1 Announce Type: new
Abstract: Language model (LM)-based speech enhancement (SE) can generate natural-sounding speech, but under severe noise it often suffers from unreliable conditioning, leading to perceptually plausible yet linguistically incorrect outputs. To address this issue, we propose L3-SE, a noise-invariant acoustic-semantic distillation framework for reducing linguistic hallucination in LM-based SE. The proposed method learns a noise-invariant conditioning encoder from noisy speech by jointly distilling two complementary clean-speech targets: an acoustic target for reconstruction fidelity and a semantic target for linguistic consistency. The resulting noise-invariant acoustic-semantic representations are used to condition a decoder-only autoregressive language model, which predicts clean acoustic tokens that are decoded into enhanced speech. To support high-quality generation, we further employ a high-fidelity codec built on learnable weighted WavLM layer representations as the discrete acoustic interface. By improving the reliability of conditioning under adverse conditions, the proposed framework substantially reduces hallucination and improves content faithfulness. Experiments show that the proposed method consistently outperforms prior LM-based speech enhancement baselines on linguistic consistency metrics, with especially clear gains under low-SNR and reverberant conditions, while maintaining competitive perceptual quality. Audio samples are available at https://max1wz.github.io/L3-SE-Demo-Page/. The complete source code will be released after the manuscript is accepted.
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BART Online Open-Source Sequence Toolbox for Computational MRI
Daniel Mackner, Philip Schaten, Markus Huemer, Viktoria Buchegger, Moritz Blumenthal, Xiaoqing Wang, Martin Uecker
https://arxiv.org/abs/2607.19099 https://arxiv.org/pdf/2607.19099 https://arxiv.org/html/2607.19099
arXiv:2607.19099v1 Announce Type: new
Abstract: Purpose In advanced computational MRI techniques, acquisition and reconstruction techniques are jointly designed. For reproducibility, it is therefore important to provide an open implementation of both. At the same time, any use in a clinical environment usually requires a close integration with the MRI scanner. Ensuring long-time reproducibility and maintenance then poses additional challenges. In this work, we aim to provide a fully integrated open-source framework that can meet these demands.
Methods A software framework to develop pulse sequences is added to the BART toolbox. In addition, a vendor-specific driver sequence is developed that can be used to run the sequence on a clinical MRI scanner enabling online adjustment of all relevant sequence parameters. Using the Pulseq format, the exact same sequence can also be reproduced offline. As proof-of-concept, quantitative MRI methods for T1 and joint water/fat R2*, B0 mapping using radial FLASH and model-based reconstruction are implemented in the proposed framework. Consistency between online and offline acquisition is validated in phantom and in vivo experiments.
Results Quantitative MRI methods consisting of acquisition and reconstruction were successfully implemented in BART. Acquisition parameters and FOV can be adapted online on a clinical MRI system. Quantitative parameter maps from model-based reconstruction agree for online and offline regenerated Pulseq acquisitions.
Conclusion This work enables reproducibility of advanced computational MRI methods within a comprehensive end-to-end open-source framework.
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interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

Packet-Loss Robust 3D Gaussian Compression via Atomic Packaging and GNN-based Error Concealment
Yuxuan Tao, Xuerui Ma, Hao Zhang, Chunhua Peng
https://arxiv.org/abs/2607.17916 https://arxiv.org/pdf/2607.17916 https://arxiv.org/html/2607.17916
arXiv:2607.17916v1 Announce Type: new
Abstract: 3D Gaussian Splatting (3DGS) and recent compression schemes such as HAC enable high-fidelity real-time neural rendering, but their bitstreams are fragile under packet loss during network streaming. Existing compression methods often separate correlated anchor attributes into independent streams, so losing one packet can create attribute-inconsistent broken anchors and severe rendering artifacts. We propose a packet-loss robust 3DGS transmission and error concealment framework. On the encoder side, anchor-level atomic packaging jointly encapsulates all attributes of each anchor, converting corrupted-attribute failures into clean missing-anchor erasures. Stratified random grouping further disperses packet losses across the spatial domain to avoid large contiguous voids. On the decoder side, we formulate recovery as prior-aware attribute inpainting. A Context-Aware Residual Interpolation (CARI) branch uses hash-grid prior predictions and neighboring residuals to build a robust baseline, while a lightweight two-layer graph neural network with cross-attention over hash-grid priors refines high-frequency attribute residuals. Attribute-wise confidence control falls back to interpolation when learned predictions are unreliable. Experiments under 20 percent random packet loss on BungeeNeRF, Mip-NeRF 360, and Tanks and Temples show that the proposed method substantially improves over no-concealment transmission and limits average PSNR degradation to about 3 dB relative to the lossless HAC reference.
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Development of a High-Performance Permanent Magnet System for Ion Trapping Experiments
Jifei Wu, Jiawei Wang, Tianhang Zhang, Zichen Su, Liangyu Huang, Wei Wu, Bingsheng Tu
https://arxiv.org/abs/2607.03255

Evaluating the Expressive Appropriateness of Speech in Rich Contexts
Tianrui Wang, Ziyang Ma, Yizhou Peng, Haoyu Wang, Zhikang Niu, Zikang Huang, Yihao Wu, Yi-Wen Chao, Yu Jiang, Yuheng Lu, Guanrou Yang, Xuanchen Li, Hexin Liu, Chunyu Qiang, Cheng Gong, Yifan Yang, Tianchi Liu, Junyu Wang, Nana Hou, Meng Ge, Fuming You, Wei Yang, Zhongqian Sun, Haifeng Hu, Xiaobao Wang, Eng Siong Chng, Xie Chen, Longbiao Wang, Jianwu Dang
https://arxiv.org/abs/2605.09413 https://arxiv.org/pdf/2605.09413 https://arxiv.org/html/2605.09413
arXiv:2605.09413v1 Announce Type: new
Abstract: Evaluating expressive speech remains challenging, as existing methods mainly assess emotional intensity and overlook whether a speech sample is expressively appropriate for its contextual setting. This limitation hinders reliable evaluation of speech systems used in narrative-driven and interactive applications, such as audiobooks and conversational agents. We introduce CEAEval, a Context-rich framework for Evaluating Expressive Appropriateness in speech, which assesses whether a speech sample expressively aligns with the underlying communicative intent implied by its discourse-level narrative context. To support this task, we construct CEAEval-D, the first context-rich speech dataset with real human performances in Mandarin conversational speech, providing narrative descriptions together with fifteen dimensions of human annotations covering expressive attributes and expressive appropriateness. We further develop CEAEval-M, a model that integrates knowledge distillation, planner-based multi-model collaboration, adaptive audio attention bias, and reinforcement learning to perform context-rich expressive appropriateness evaluation. Experiments on a human-annotated test set demonstrate that CEAEval-M substantially outperforms existing speech evaluation and analysis systems.
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celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 2724 nodes and 14322 edges.
Tags: Biological, Protein interactions, Unweighted…

EVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain Database
Kaiyuan Tang, Maizhe Yang, Chaoli Wang
https://arxiv.org/abs/2607.18187 https://arxiv.org/pdf/2607.18187 https://arxiv.org/html/2607.18187
arXiv:2607.18187v1 Announce Type: new
Abstract: Large-scale scientific simulations generate volumetric data at rates that far outpace advances in storage and network bandwidth, making effective lossy compression increasingly critical. However, conventional compressors often struggle to preserve fine structural details at high compression ratios (CRs), and implicit neural representations (INRs) require costly per-volume optimization and produce models with fixed CRs. To respond, we present EVOLVE, an autoencoder (AE)-based volume-compression framework that targets high CRs for offline compression, with three key contributions. First, we construct a large-scale cross-domain database of 6,376 volumes from 21 scientific simulations, curated via perceptual hashing to ensure diversity, enabling the optimized model to extract features that generalize across volumes within the covered scientific simulation domains. Second, we reexamine the design space of AE-based compressors and incorporate several macro- and micro-designs into a vanilla AE to develop EVOLVE, which substantially improves the expressive power and compression capability. Third, we develop a learnable gain mechanism with a three-stage training strategy to enable variable-rate encoding, allowing a single model to support continuous CR adjustment at inference time. Experiments on multiple unseen scientific simulation datasets demonstrate that EVOLVE achieves substantially higher CRs than conventional compressors at comparable reconstruction quality, while delivering compression speeds that are orders of magnitude faster than INR-based methods, highlighting its promise as a strong alternative for compressing scientific data. The code, model weights, and results are available on our project page at https://evolve-vis.github.io.
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Information Transport and Observability in Compressible Aerodynamics
Bo Zhang
https://arxiv.org/abs/2607.20177 https://arxiv.org/pdf/2607.20177 https://arxiv.org/html/2607.20177
arXiv:2607.20177v1 Announce Type: new
Abstract: Pressure measurements provide sparse but direct observations of compressible aerodynamic flows, yet how information about hidden aerodynamic parameters is transported through the flow and encoded in these observations remains poorly understood. Here, we investigate information transport and observability in compressible aerodynamics using a differentiable shock-capturing immersed-boundary solver. By propagating gradients through the full unsteady flow solution, an automatic-differentiation-based observability metric is introduced to quantify the sensitivity of sparse pressure measurements to unknown aerodynamic parameters and identify informative sensing locations for inverse learning. The results reveal that aerodynamic information is transported non-uniformly through the flow field, producing localized regions of high observability. Inverse-learning experiments further demonstrate that observability and learnability are related but distinct concepts: although highly observable probes generally facilitate accurate parameter recovery, the highest-observability probe is not consistently the most effective for parameter inference. Furthermore, both the flow regime and the airfoil geometry substantially influence the distribution of observability and the convergence behavior of inverse learning. These findings establish a quantitative framework for understanding how aerodynamic information is encoded in sparse measurements and demonstrate the potential of automatic differentiation for observability analysis, informative sensor selection, and aerodynamic inverse analysis.
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celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 2528 nodes and 3864 edges.
Tags: Biological, Protein interactions, Unweighted

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 1237 nodes and 1735 edges.
Tags: Biological, Protein interactions, Unweighted

Text2Villa: Hierarchical Generation of 3D Indoor Environments with Physics-Aware Analysis-by-Synthesis
Xiang Tang, Ruotong Li, Xiaopeng Fan
https://arxiv.org/abs/2607.17145 https://arxiv.org/pdf/2607.17145 https://arxiv.org/html/2607.17145
arXiv:2607.17145v1 Announce Type: new
Abstract: Generating 3D indoor scenes from natural language holds tremendous potential, yet existing methods predominantly fail to generate multi-room structures with vertical connectivity and arbitrary polygonal boundaries. Furthermore, they lack a deep grounding in continuous 3D physical laws, leading to severe geometric penetrations and floating artifacts. In this work, we propose Text2Villa, a novel hierarchical generative framework. At the macro level, we construct a multi-story dataset to fine-tune an autoregressive layout generator, ensuring the direct parsing of text into 3D building foundations featuring polygonal boundaries and multi-story connectivity. To enforce physical laws during micro-level asset arrangement, we introduce the Affordance-driven Physical-Semantic Scene Graph (A-PSSG) to explicitly abstract physical affordances (such as support surfaces and containment cavities) into node attributes, establishing strict geometric and semantic edge constraints. Guided by the A-PSSG, we formulate scene instantiation as a constrained closed-loop optimization problem following the analysis-by-synthesis paradigm. By integrating an underlying geometric collision detection engine with the high-level semantic reasoning of multimodal large language models (MLLMs), our heuristic solver dynamically executes physics-aware actions under the observation-evaluation-modification mechanism to effectively resolve mesh collisions, floating artifacts, and fine-grained cavity containment failures. Extensive experiments demonstrate that Text2Villa outperforms previous methods across various metrics, robustly generating high-fidelity and physically plausible villa-level 3D environments from text, thereby providing a reliable and interactive 3D content foundation for downstream applications.
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celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 912 nodes and 22738 edges.
Tags: Biological, Protein interactions, Unweighted

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 6176 nodes and 178151 edges.
Tags: Biological, Protein interactions, Unweighte…

interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 2528 nodes and 3864 edges.
Tags: Biological, Protein interactions, Unweighted

interactome_stelzl: Stelzl human interactome (2005)
A network of human proteins and their binding interactions. Nodes represent proteins and an edge represents an interaction between two proteins, as inferred via high-throughput Y2H experiments using bait and prey methodology.
This network has 1706 nodes and 6207 edges.
Tags: Biological, Protein interactions, Unweighted