Tootfinder

Ukraine to mass produce long-range Flamingo missile in winter, Zelensky says: https://benborges.xyz/2025/08/21/ukraine-to-mass-produce-longrange.html

Research: low productivity gains from AI may stem from employees using AI to produce "workslop", or low-effort, passable work that creates more work for others (Harvard Business Review)
https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivit…

AI-Generated “Workslop” Is Destroying Productivity
Despite a surge in generative AI use across workplaces, most companies are seeing little measurable ROI. One possible reason is because AI tools are being used to produce “workslop”—content that appears polished but lacks real substance, offloading cognitive labor onto coworkers. Research from BetterUp Labs and Stanford found that 41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and colla…

By engineering yeast to produce six essential sterols found in pollen, researchers provided bees with a nutritionally complete diet that boosted reproduction up to 15-fold.
Unlike commercial substitutes that lack key nutrients, this supplement mimics natural pollen’s sterol profile, giving bees the equivalent of a balanced diet.
…

Scientists found the missing nutrients bees need — Colonies grew 15-fold
Scientists have developed a breakthrough food supplement that could help save honeybees from devastating declines. By engineering yeast to produce six essential sterols found in pollen, researchers provided bees with a nutritionally complete diet that boosted reproduction up to 15-fold. Unlike commercial substitutes that lack key nutrients, this supplement mimics natural pollen’s sterol profile, giving bees the equivalent of a balanced diet.

Do AI models help produce verified bug fixes?
Li Huang, Ilgiz Mustafin, Marco Piccioni, Alessandro Schena, Reto Weber, Bertrand Meyer
https://arxiv.org/abs/2507.15822

Do AI models help produce verified bug fixes?
Among areas of software engineering where AI techniques -- particularly, Large Language Models -- seem poised to yield dramatic improvements, an attractive candidate is Automatic Program Repair (APR), the production of satisfactory corrections to software bugs. Does this expectation materialize in practice? How do we find out, making sure that proposed corrections actually work? If programmers have access to LLMs, how do they actually use them to complement their own skills? To answer these q…

"Low effort, unhelpful AI generated work is having a significant impact on collaboration at work. Approximately half of the people we surveyed viewed colleagues who sent workslop as less creative, capable, and reliable than they did before receiving the output. Forty-two percent saw them as less trustworthy, "
(Original title: AI-Generated “Workslop” Is Destroying Productivity)

AI-Generated “Workslop” Is Destroying Productivity
Despite a surge in generative AI use across workplaces, most companies are seeing little measurable ROI. One possible reason is because AI tools are being used to produce “workslop”—content that appears polished but lacks real substance, offloading cognitive labor onto coworkers. Research from BetterUp Labs and Stanford found that 41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and colla…

When brewing kombucha, make sure to end fermentation at the right time! Yeasts produce alcohol as a byproduct of fermentation, and the alcohol level can get high enough that they will pop out for a cheeky nando's and contaminate the brew with piri piri flavor

Sometimes innovation is quite simple 🙂
""Our measurements show that wheat and grass-clover mixtures grow just as well between vertical solar panels as in open fields. At the same time, the panels produce electricity in a daily pattern that better matches energy demand. It's a win-win,"
#solarpanels

Double harvest: Vertical solar panels and crops thrive side by side
Imagine a field where solar panels and crops coexist—with no trade-off. It sounds like science fiction, but that's precisely what researchers from Aarhus University have now documented in a full-scale agrivoltaic pilot project in the Danish countryside.

A senior CIA officer who oversaw Russia analysis
has been stripped of her security clearance,
part of a sweeping removal of
37 serving and former officials accused of "betray[ing] their oath to the Constitution," the Economist reported on Aug. 21.
The officer, who served as the CIA’s top Russia and Eurasia analyst during the 2016 election
and helped produce the report detailing Moscow’s interference on behalf of Donald Trump,
was among the most s…

Trump administration escalates purge of senior US intelligence officials, Economist reports
The officer, who served as the CIA’s top Russia and Eurasia analyst during the 2016 election and helped produce the report detailing Moscow’s interference on behalf of Donald Trump, was among the most senior career officials targeted.

A classic. Reporter fails to pay attention to what the nimbys actually say.
Reporter: Critics fear that [very modest] upzone won't produce "housing that is actually affordable for county residents"
Then quotes critic who fears it will "just provide more affordably priced rental units"
https://…

Jag har märkt att många tror att de får bra svar från olika AI verktyg när de i själva verket bara bekräftar det som användaren vill ha bekräftat.
OpenAI researchers reveal that large language models will always produce plausible but false outputs, even with perfect data, due to fundamental statistical and computational limits.

OpenAI admits AI hallucinations are mathematically inevitable, not just engineering flaws
In a landmark study, OpenAI researchers reveal that large language models will always produce plausible but false outputs, even with perfect data, due to fundamental statistical and computational limits.

AI-Generated “Workslop” Is Destroying Productivity https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity

AI-Generated “Workslop” Is Destroying Productivity
Despite a surge in generative AI use across workplaces, most companies are seeing little measurable ROI. One possible reason is because AI tools are being used to produce “workslop”—content that appears polished but lacks real substance, offloading cognitive labor onto coworkers. Research from BetterUp Labs and Stanford found that 41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and colla…

What ingests large quantities of data, applies some math and outputs a much smaller set of data that can still be used to reconstruct what was ingested? Compression algorithms, right?
And some of them compress *so much* that data can only be extracted partially and the rest needs to be "guessed" - like JPEGs.
LLMs ingest TB after TB and compress that into a few miserable GB.
And that's why the info they produce is like a JPEG with a compression factor of 1000 and…

An open dataset of neural networks for hypernetwork research
David Kurtenbach, Lior Shamir
https://arxiv.org/abs/2507.15869 https://a…

An open dataset of neural networks for hypernetwork research
Despite the transformative potential of AI, the concept of neural networks that can produce other neural networks by generating model weights (hypernetworks) has been largely understudied. One of the possible reasons is the lack of available research resources that can be used for the purpose of hypernetwork research. Here we describe a dataset of neural networks, designed for the purpose of hypernetworks research. The dataset includes $10^4$ LeNet-5 neural networks trained for binary image cla…

Sam Altman says OpenAI wants to create "a factory that can produce a gigawatt of new AI infrastructure every week" and plans to reveal more details this year (Sam Altman)
https://blog.samaltman.com/abundant-intelligence

LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoning
Bo Hou, Xin Tan, Kai Zheng, Fang Liu, Yinghao Zhu, Li Zhang
https://arxiv.org/abs/2507.16395

LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoning
Atomic commits, each of which addresses a single development concern, are a best practice in software development. However, developers frequently produce tangled commits that mix unrelated changes due to practical constraints or unclear boundaries, negatively impacting code review and maintenance. Although prior commit untangling approaches: rule-based, feature-based, or graph-based, have made progress, they often rely on shallow signals and fail to distinguish between explicit dependencies (e.…

Reservoir Computing as a Language Model
Felix K\"oster, Atsushi Uchida
https://arxiv.org/abs/2507.15779 https://arxiv.org/pdf/25…

Reservoir Computing as a Language Model
Large Language Models (LLM) have dominated the science and media landscape duo to their impressive performance on processing large chunks of data and produce human-like levels of text. Nevertheless, their huge energy demand and slow processing still a bottleneck for further increasing quality while also making the models accessible to everyone. To solve this bottleneck, we will investigate how reservoir computing performs on natural text processing, which could enable fast and energy efficient …

"A confusing contradiction is unfolding in companies embracing generative AI tools: while workers are largely following mandates to embrace the technology, few are seeing it create real value. [...] In collaboration with Stanford Social Media Lab, our research team at BetterUp Labs has identified one possible reason: Employees are using AI tools to create low-effort, passable looking work that ends up creating more work for their coworkers."
"Unlike this mental outsourc…

AI-Generated “Workslop” Is Destroying Productivity
Despite a surge in generative AI use across workplaces, most companies are seeing little measurable ROI. One possible reason is because AI tools are being used to produce “workslop”—content that appears polished but lacks real substance, offloading cognitive labor onto coworkers. Research from BetterUp Labs and Stanford found that 41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and colla…

MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer
Yanghao Li, Rui Qian, Bowen Pan, Haotian Zhang, Haoshuo Huang, Bowen Zhang, Jialing Tong, Haoxuan You, Xianzhi Du, Zhe Gan, Hyunjik Kim, Chao Jia, Zhenbang Wang, Yinfei Yang, Mingfei Gao, Zi-Yi Dou, Wenze Hu, Chang Gao, Dongxu Li, Philipp Dufter, Zirui Wang, Guoli Yin, Zhengdong Zhang, Chen Chen, Yang Zhao, Ruoming Pang, Zhifeng Chen

MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer
Unified multimodal Large Language Models (LLMs) that can both understand and generate visual content hold immense potential. However, existing open-source models often suffer from a performance trade-off between these capabilities. We present Manzano, a simple and scalable unified framework that substantially reduces this tension by coupling a hybrid image tokenizer with a well-curated training recipe. A single shared vision encoder feeds two lightweight adapters that produce continuous embeddi…

"Floating platform to produce synthetic fuels using wind, seawater, and air"
#Energy #Renewables
https://

Floating platform to produce synthetic fuels using wind, seawater, and air
Off-grid, modular, and seaworthy: KIT (Karlsruhe Institute of Technology) and partners intend to produce synthetic fuels on a floating platform using wind energy, seawater, and ambient air. For this purpose, the "PtX-Wind" project was launched under the H2Mare lead project. A corresponding modular plant was installed on a barge and lies operational at anchor in Bremerhaven. Later this year, it will start producing synthetic fuel directly on the sea just off Helgoland Island.

The Iconicity of the Generated Image
Nanne van Noord, Noa Garcia
https://arxiv.org/abs/2509.16473 https://arxiv.org/pdf/2509.16473

The Iconicity of the Generated Image
How humans interpret and produce images is influenced by the images we have been exposed to. Similarly, visual generative AI models are exposed to many training images and learn to generate new images based on this. Given the importance of iconic images in human visual communication, as they are widely seen, reproduced, and used as inspiration, we may expect that they may similarly have a proportionally large influence within the generative AI process. In this work we explore this question thro…

AEAS: Actionable Exploit Assessment System
Xiangmin Shen, Wenyuan Cheng, Yan Chen, Zhenyuan Li, Yuqiao Gu, Lingzhi Wang, Wencheng Zhao, Dawei Sun, Jiashui Wang
https://arxiv.org/abs/2509.17832

AEAS: Actionable Exploit Assessment System
Security practitioners face growing challenges in exploit assessment, as public vulnerability repositories are increasingly populated with inconsistent and low-quality exploit artifacts. Existing scoring systems, such as CVSS and EPSS, offer limited support for this task. They either rely on theoretical metrics or produce opaque probability estimates without assessing whether usable exploit code exists. In practice, security teams often resort to manual triage of exploit repositories, which is …

Certifiably Optimal Doppler Positioning using Opportunistic LEO Satellites
Baoshan Song, Weisong Wen, Qi Zhang, Bing Xu, Li-Ta Hsu
https://arxiv.org/abs/2509.17198 https://

Certifiably Optimal Doppler Positioning using Opportunistic LEO Satellites
To provide backup and augmentation to global navigation satellite system (GNSS), Doppler shift from Low Earth Orbit (LEO) satellites can be employed as signals of opportunity (SOP) for position, navigation and timing (PNT). Since the Doppler positioning problem is non-convex, local searching methods may produce two types of estimates: a global optimum without notice or a local optimum given an inexact initial estimate. As exact initialization is unavailable in some unknown environments, a guara…

Evaluating classical simulations with a quantum processor
Alberto Nocera, Jack Raymond, William Bernoudy, Mohammad H. Amin, Andrew D. King
https://arxiv.org/abs/2508.15759 https…

Evaluating classical simulations with a quantum processor
As simulations of quantum systems cross the limits of classical computability, both quantum and classical approaches become hard to verify. Scaling predictions are therefore based on local structure and asymptotic assumptions, typically with classical methods being used to evaluate quantum simulators where possible. Here, in contrast, we use a quantum annealing processor to produce a ground truth for evaluating classical tensor-network methods whose scaling has not yet been firmly established. …

Surfacing Variations to Calibrate Perceived Reliability of MLLM-generated Image Descriptions
Meng Chen, Akhil Iyer, Amy Pavel
https://arxiv.org/abs/2507.15692

Surfacing Variations to Calibrate Perceived Reliability of MLLM-generated Image Descriptions
Multimodal large language models (MLLMs) provide new opportunities for blind and low vision (BLV) people to access visual information in their daily lives. However, these models often produce errors that are difficult to detect without sight, posing safety and social risks in scenarios from medication identification to outfit selection. While BLV MLLM users use creative workarounds such as cross-checking between tools and consulting sighted individuals, these approaches are often time-consuming…

Pete Carroll's Plans for the Raiders' Rookies https://www.si.com/nfl/raiders/news/pete-carroll-ashton-jeanty-training-camp-donte-thornton-jack-bech-nfl

Parameter variability can produce heavy tails in a model for the spatial distribution of settling organisms
Luis F. Gordillo, Priscilla E. Greenwood
https://arxiv.org/abs/2509.16385

Parameter variability can produce heavy tails in a model for the spatial distribution of settling organisms
We show that a simple mechanistic model of spatial dispersal for settling organisms, subject to parameter variability, can generate heavy-tailed radial probability density functions. The movement of organisms in the model consists of a two-dimensional diffusion that ceases after a random time, where the parameters that characterize each of these stages have been randomized. Our findings show that these minimal assumptions can yield heavy-tailed dispersal patterns, providing a simplified framewo…

Any-Dimensional Polynomial Optimization via de Finetti Theorems
Eitan Levin, Venkat Chandrasekaran
https://arxiv.org/abs/2507.15632 https://

Any-Dimensional Polynomial Optimization via de Finetti Theorems
Polynomial optimization problems often arise in sequences indexed by dimension, and it is of interest to produce bounds on the optimal values of all problems in the sequence. Examples include certifying inequalities between symmetric functions or graph homomorphism densities that hold over vectors and graphs of all sizes, and computing the value of mean-field games viewed as limits of games with a growing number of players. In this paper, we study such any-dimensional polynomial problems using …

Domino tilings, nonintersecting lattice paths and subclasses of Koutschan-Krattenthaler-Schlosser determinants
Qipin Chen, Shane Chern, Atsuro Yoshida
https://arxiv.org/abs/2507.15665

Domino tilings, nonintersecting lattice paths and subclasses of Koutschan-Krattenthaler-Schlosser determinants
Koutschan, Krattenthaler and Schlosser recently considered a family of binomial determinants. In this work, we give combinatorial interpretations of two subclasses of these determinants in terms of domino tilings and nonintersecting lattice paths, thereby partially answering a question of theirs. Furthermore, the determinant evaluations established by Koutschan, Krattenthaler and Schlosser produce many product formulas for our weighted enumerations of domino tilings and nonintersecting lattice …

TTMBA: Towards Text To Multiple Sources Binaural Audio Generation
Yuxuan He, Xiaoran Yang, Ningning Pan, Gongping Huang
https://arxiv.org/abs/2507.16564 ht…

TTMBA: Towards Text To Multiple Sources Binaural Audio Generation
Most existing text-to-audio (TTA) generation methods produce mono outputs, neglecting essential spatial information for immersive auditory experiences. To address this issue, we propose a cascaded method for text-to-multisource binaural audio generation (TTMBA) with both temporal and spatial control. First, a pretrained large language model (LLM) segments the text into a structured format with time and spatial details for each sound event. Next, a pretrained mono audio generation network create…

Fast approximate Bayesian inference of HIV indicators using PCA adaptive Gauss-Hermite quadrature
Adam Howes, Alex Stringer, Seth R. Flaxman, Jeffrey W. Imai-Eaton
https://arxiv.org/abs/2508.15665

Fast approximate Bayesian inference of HIV indicators using PCA adaptive Gauss-Hermite quadrature
Naomi is a spatial evidence synthesis model used to produce district-level HIV epidemic indicators in sub-Saharan Africa. Multiple outcomes of policy interest, including HIV prevalence, HIV incidence, and antiretroviral therapy treatment coverage are jointly modelled using both household survey data and routinely reported health system data. The model is provided as a tool for countries to input their data to and generate estimates with during a yearly process supported by UNAIDS. Previously, i…

TACO Trump Reverses Course, Directs Bondi to Produce Meaningless Epstein Files - WhoWhatWhy
https://whowhatwhy.org/politics/us-politics/taco-trump-reverses-course-directs-bondi-to-produce-meaningless-epstein-files/

I noticed a weird technology gap: Funders like @… or @… have started to require Gantt charts for funding applications, yet there seems to be no established way to produce them. Yes, there’s MS Project and the like, but no s…

MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction
Zilin Xiao, Qi Ma, Mengting Gu, Chun-cheng Jason Chen, Xintao Chen, Vicente Ordonez, Vijai Mohan
https://arxiv.org/abs/2509.18095

MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction
Universal multimodal embedding models have achieved great success in capturing semantic relevance between queries and candidates. However, current methods either condense queries and candidates into a single vector, potentially limiting the expressiveness for fine-grained information, or produce too many vectors that are prohibitively expensive for multi-vector retrieval. In this work, we introduce MetaEmbed, a new framework for multimodal retrieval that rethinks how multimodal embeddings are c…

Remote Channel Synthesis
Yassine Hamdi, Deniz G\"und\"uz
https://arxiv.org/abs/2507.15757 https://arxiv.org/pdf/2507.15757

Remote Channel Synthesis
We consider the problem of synthesizing a memoryless channel between an unobserved source and a remote terminal. An encoder has access to a partial or noisy version $Z^n = (Z_1, \ldots, Z_n)$ of a remote source sequence $X^n = (X_1, \ldots, X_n),$ with $(X_i,Z_i)$ independent and identically distributed with joint distribution $q_{X,Z}.$ The encoder communicates through a noiseless link to a decoder which aims to produce an output $Y^n$ coordinated with the remote source; that is, the total var…

"Ohio Bill Would Require Watermarks on AI Imagery"
How exactly does a state enforce this? 🤔 "...it could place restrictions on a consumer's legal uses of a product, or it could place restrictions on what type of functions a producer's product can actually produce."
http…

Role of sunspot latitude versus tilt in determining the polar field and amplitude of the next cycle: Cause of the weak Solar Cycle 20
Bidisha Dey, Anu Sreedevi, Bidya Binay Karak
https://arxiv.org/abs/2509.17146

Role of sunspot latitude versus tilt in determining the polar field and amplitude of the next cycle: Cause of the weak Solar Cycle 20
One prominent feature of solar cycle is its irregular variation in its cycle strength, making it challenging to predict the amplitude of the next cycle. Studies show that fluctuations and nonlinearity in generating poloidal field throughout the decay and dispersal of tilted sunspots produce variation in the solar cycle. The flux, latitudinal position, and tilt angle of sunspots are the primary parameters that determine the polar field and, thus, the next solar cycle strength. By analysing the o…

Impact of Packetization on Network Calculus Analysis
Yming Jiang
https://arxiv.org/abs/2509.17028 https://arxiv.org/pdf/2509.17028

Impact of Packetization on Network Calculus Analysis
For packet-switched networks, when the packetization effect is overlooked, network calculus analysis can produce faulty results. To exemplify, network calculus analysis is applied in this paper to two basic systems that are fundamental or default settings in Time-Sensitive Networking (TSN) and Deterministic Networking (DetNet). Through counterexamples, it is revealed that for the two fundamental settings, some widely adopted, network calculus-based service characterization results, known as ser…

Smoothing topological pseudo-isotopies of 4-manifolds
Patrick Orson, Mark Powell, Oscar Randal-Williams
https://arxiv.org/abs/2507.16984 https://arxiv.org/…

Smoothing topological pseudo-isotopies of 4-manifolds
Given a closed, smooth 4-manifold $X$ and self-diffeomorphism $f$ that is topologically pseudo-isotopic to the identity, we study the question of whether $f$ is moreover smoothly pseudo-isotopic to the identity. If the fundamental group of $X$ lies in a certain class, which includes trivial, free, and finite groups of odd order, we show the answer is always affirmative. On the other hand, we produce the first examples of manifolds $X$ and diffeomorphisms $f$ where the answer is negative. Our in…

State Space Models Naturally Produce Traveling Waves, Time Cells, and Scale to Abstract Cognitive Functions
Sen Lu, Xiaoyu Zhang, Mingtao Hu, Eric Yeu-Jer Lee, Soohyeon Kim, Wei D. Lu
https://arxiv.org/abs/2507.13638

State Space Models Naturally Produce Traveling Waves, Time Cells, and Scale to Abstract Cognitive Functions
A grand challenge in modern neuroscience is to bridge the gap between the detailed mapping of microscale neural circuits and a mechanistic understanding of cognitive functions. While extensive knowledge exists about neuronal connectivity and biophysics, a significant gap remains in how these elements combine to produce flexible, learned behaviors. Here, we propose that a framework based on State-Space Models (SSMs), an emerging class of deep learning architectures, can bridge this gap. We argue…

“Produce”? I guess that Pentagon contract with Grok will get its first use.
https://www.bbc.com/news/articles/c9w1014rlq9o

Donald Trump orders US attorney general to 'produce' more Epstein documents
Trump's supporters and opponents alike have demanded more disclosures related to the disgraced financier.

Artifacts in Halo Shapes: Imprints of the Initial Condition
Yu Yu, Zhao Chen
https://arxiv.org/abs/2507.16745 https://arxiv.org/pdf/2…

Artifacts in Halo Shapes: Imprints of the Initial Condition
Grid type pre-initial conditions are commonly used to initialize particle positions in cosmological simulations. While these conditions are known to produce noticeable numerical artifacts in void regions, their impact on halo properties has generally been assumed to be negligible. In this work, we employ multiple simulations to demonstrate that grid initialization induces statistically significant artifacts in halo shapes, despite the modest absolute amplitude ($\sim 1\%$) making them unimporta…

Discrete Empirical Interpolation Method with Upper and Lower Bound Constraints
Louisa B. Ebby, Mohammad Farazmand
https://arxiv.org/abs/2509.16018 https://…

Discrete Empirical Interpolation Method with Upper and Lower Bound Constraints
Discrete Empirical Interpolation Method (DEIM) is a simple and effective method for reconstructing a function from its incomplete pointwise observations. However, applying DEIM to functions with physically constrained ranges can produce reconstructions with values outside the prescribed physical bounds. Such physically constrained quantities occur routinely in applications, e.g., mass density whose range is nonnegative. The DEIM reconstructions which violate these physical constraints are not u…

A Generative Model for Disentangling Galaxy Photometric Parameters
Keen Leung, Colen Yan, Jun Yin
https://arxiv.org/abs/2507.15898 https://

A Generative Model for Disentangling Galaxy Photometric Parameters
Ongoing and future photometric surveys will produce unprecedented volumes of galaxy images, necessitating robust, efficient methods for deriving galaxy morphological parameters at scale. Traditional approaches, such as parametric light-profile fitting, offer valuable insights but become computationally prohibitive when applied to billions of sources. In this work, we propose a Conditional AutoEncoder (CAE) framework to simultaneously model and characterize galaxy morphology. Our CAE is trained …

Separable cowreaths in higher dimension
Fabio Renda
https://arxiv.org/abs/2506.18762 https://arxiv.org/pdf/2506.18762

Separable cowreaths in higher dimension
In this paper we present an infinite family of (h-)separable cowreaths with increasing dimension. Menini and Torrecillas proved in [20] that for $A=Cl(α,β, γ)$, a four-dimensional Clifford algebra, and $H=H_4$, Sweedler's Hopf algebra, the cowreath $(A \otimes H^{op},H, ψ)$ is always (h-)separable. We show how to produce similar examples in higher dimension by considering a $2^{n+1}$-dimensional Clifford algebra $A=Cl(α,β_i,γ_i,λ_{ij})$ and $H=E(n)$, a suitable pointed Hopf algebra that…

Zonal winds in Titan's middle atmosphere from a stellar occultation observed with Keck adaptive optics
Theresa C. Marlin, Eliot F. Young, Katherine de Kleer, Martin Cordiner, Nicholas A. Lombardo, Imke de Pater, Juan M. Lora, Paul Corlies, Richard Cosentino, Conor Nixon, Sebastien Rodriguez, Alexander Thelen
https://arxiv.org/abs/2509.…

Zonal winds in Titan's middle atmosphere from a stellar occultation observed with Keck adaptive optics
We present spatially resolved Keck/NIRC2 images of a stellar occultation by Titan on September 5, 2022 and compare them to predictions from concurrent ALMA observations and a suite of General Circulation Model (GCM) simulations. ALMA data and GCM simulations can predict middle atmosphere zonal wind distributions, which in turn produce diagnostic occultation image sequences. We construct an occultation forward model using the temperature profile measured by the Huygens Atmospheric Structure Inst…

pH-dependent interfacial rheology of polymer membranes assembled at liquid-liquid interfaces using hydrogen bonds
Julien Dupr\'e de Baubigny (SIMM), Corentin Tregouet (SIMM), Elena N. Govorun (SIMM), Mathilde Reyssat (SIMM), Patrick Perrin (SIMM), Nad\`ege Pantoustier (SIMM), Thomas Salez (LOMA), C\'ecile Monteux (SIMM)
https://arx…

pH-dependent interfacial rheology of polymer membranes assembled at liquid-liquid interfaces using hydrogen bonds
Self-assembly of polymers at liquid interfaces using non-covalent interactions has emerged as a promising technique to reversibly produce self-healing membranes. Besides the assembly process, it is also crucial to control the mechanical properties of these membranes. Here, we measure the interfacial rheological properties of PMAA-PPO (polymethacrylic acidpolypropylene oxide) polymer membranes assembled using hydrogen bonds at liquid-oil interfaces. Varying the pH enables us to modify the degree…

Critical bubble bursting in real water. Effect of surface-active contaminants
S. Rodr\'iguez-Aparicio, A. Cebri\'an-Garc\'ia, E. J. Vega, J. M. Montanero, M. G. Cabezas
https://arxiv.org/abs/2507.17671

Critical bubble bursting in real water. Effect of surface-active contaminants
We study the bubble bursting under critical conditions, i.e., those leading to the minimum (maximum) size (velocity) of the first-emitted jet droplet. Our experiments show that a tiny amount of surfactant considerably increases (decreases) the droplet radius (velocity). The volume of the first-emitted droplet increases by a factor of 20 in the presence of surfactant, even for concentrations that produce an insignificant reduction in the bubble surface tension. Surfactant accumulates at the bubb…

Effect of radial pressure corrugations and profile shearing on turbulence in Fusion plasmas
Ajay C. J, M. J. Pueschel, Justin Ball, David Hatch, Tobias Goerler, Stephan Brunner
https://arxiv.org/abs/2507.15513

Effect of radial pressure corrugations and profile shearing on turbulence in Fusion plasmas
Microturbulence can produce stationary fine-scale radial corrugations on the plasma density and temperature gradients in magnetic confinement fusion devices. We show that these structures play a significant role in regulating turbulent transport. We focus on the pedestal, studying electron-temperature-gradient (ETG) mode destabilisation and saturation in the presence of radial corrugations on the electron temperature gradient that could result from microtearing turbulence. A linear dispersion r…

💩 A more climate-friendly way to produce nitrogen fertilizer
#chemistry

A more climate-friendly way to produce nitrogen fertilizer
Humanity has an insatiable appetite for ammonia: This substance is used to make fertilizer, which in turn is used in most modern agriculture. Until now, the Haber-Bosch process has been the method of choice for extracting nitrogen from the seemingly inexhaustible atmosphere and binding it in the form of ammonia. However, this method requires an extremely large amount of methane gas and energy.

Bustling 🫜
攒动 🫜
📷 Nikon FE
🎞️FOMAPAN Action 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Auto-Regressive Surface Cutting
Yang Li, Victor Cheung, Xinhai Liu, Yuguang Chen, Zhongjin Luo, Biwen Lei, Haohan Weng, Zibo Zhao, Jingwei Huang, Zhuo Chen, Chunchao Guo
https://arxiv.org/abs/2506.18017

Auto-Regressive Surface Cutting
Surface cutting is a fundamental task in computer graphics, with applications in UV parameterization, texture mapping, and mesh decomposition. However, existing methods often produce technically valid but overly fragmented atlases that lack semantic coherence. We introduce SeamGPT, an auto-regressive model that generates cutting seams by mimicking professional workflows. Our key technical innovation lies in formulating surface cutting as a next token prediction task: sample point clouds on mesh…

An analytic formalism to describe the $N_{\rm eff}(\rm H)$-$n_{\rm H}$ relationship in molecular clouds
Brandt A. L. Gaches
https://arxiv.org/abs/2507.16931

An analytic formalism to describe the $N_{\rm eff}(\rm H)$-$n_{\rm H}$ relationship in molecular clouds
Context. Astrochemical modeling requires, as input, the effective column density of gas (or extinction) that attenuates an external, isotropic, far-ultraviolet radiation field. In three-dimensional simulations, this can be calculated through ray-tracing schemes, while in 0D chemical models it is often treated as a free parameter. Aims. We aim to produce an analytic, physically motivated formalism to predict the average relationship between the effective hydrogen-nuclei column density, $N_{\rm e…

Vamos a utilizar una tecnología que comete errores de forma irreparable por culpa del propio diseño en sí de la tecnología.
Ya me imagino a la gente montando en un avión que puede que llegue al destino o que se precipite contra una montaña, no se sabe. https:/…

Moire Artifact Reduction in Grating Interferometry Using Multiple Harmonics and Total Variation Regularization
Hunter C. Meyer, Joyoni Dey, Conner B. Dooley, Murtuza S. Taqi, Varun R. Gala, Christopher Morrison, Victoria L. Fontenot, Kyungmin Ham, Leslie G. Butler, Alexandra Noel
https://arxiv.org/abs/2509.16503

Moire Artifact Reduction in Grating Interferometry Using Multiple Harmonics and Total Variation Regularization
X-ray interferometry is an emerging imaging modality with a wide range of potential clinical applications, including lung and breast imaging, as well as non destructive testing in fields such as additive manufacturing and porosimetry. A grating interferometer uses a diffraction grating to produce a periodic interference pattern and measures how a patient or sample perturbs the pattern, producing three unique images that highlight X-ray absorption, refraction, and small angle scattering, known a…

Technical overview and architecture of the FastNet Machine Learning weather prediction model, version 1.0
Eric G. Daub, Tom Dunstan, Thusal Bennett, Matthew Burnand, James Chappell, Alejandro Coca-Castro, Noushin Eftekhari, J. Scott Hosking, Manvendra Janmaijaya, Jon Lillis, David Salvador-Jasin, Nathan Simpson, Oliver T Strickson, Ryan Sze-Yin Chan, Mohamad Elmasri, Lydia Allegranza France, Sam Madge, James Robinson, Adam A. Scaife, David Walters, Peter Yatsyshin, Theo McCaie, Levan B…

Technical overview and architecture of the FastNet Machine Learning weather prediction model, version 1.0
We present FastNet version 1.0, a data-driven medium range numerical weather prediction (NWP) model based on a Graph Neural Network architecture, developed jointly between the Alan Turing Institute and the Met Office. FastNet uses an encode-process-decode structure to produce deterministic global weather predictions out to 10 days. The architecture is independent of spatial resolution and we have trained models at 1$^{\circ}$ and 0.25$^{\circ}$ resolution, with a six hour time step. FastNet use…

Beyond papers: understanding the making of citizenship in the Foreigners’ Tribunals of Assam
https://ift.tt/07U3HFa
Fariya Yesmin's new article Beyond papers: understanding the making of citizenship in the…
via Input 4 RELCFP

Beyond papers: understanding the making of citizenship in the Foreigners’ Tribunals of Assam
Fariya Yesmin's new article Beyond papers: understanding the making of citizenship in the Foreigners’ Tribunals of Assam has been published by Contemporary South Asia. You can download the full article here. AbstractThis paper questions the hyper fixation on papers in producing citizens or proving citizenship, arguing that not papers but the agglomeration of legal, bureaucratic and social processes produce citizenship in Assam’s Foreigners’ Tribunals (FTs). Based on ethnographic fieldwork…

Improving the Generation of VAEs with High Dimensional Latent Spaces by the use of Hyperspherical Coordinates
Alejandro Ascarate, Leo Lebrat, Rodrigo Santa Cruz, Clinton Fookes, Olivier Salvado
https://arxiv.org/abs/2507.15900

Improving the Generation of VAEs with High Dimensional Latent Spaces by the use of Hyperspherical Coordinates
Variational autoencoders (VAE) encode data into lower-dimensional latent vectors before decoding those vectors back to data. Once trained, decoding a random latent vector from the prior usually does not produce meaningful data, at least when the latent space has more than a dozen dimensions. In this paper, we investigate this issue by drawing insight from high dimensional statistics: in these regimes, the latent vectors of a standard VAE are by construction distributed uniformly on a hyperspher…

Scanning Tunneling Microscope Tip-Induced Formation of Bi Bilayers on Bi$_2$Te$_3$
Duy Nguyen, Jay A. Gupta
https://arxiv.org/abs/2507.16081 https://

Scanning Tunneling Microscope Tip-Induced Formation of Bi Bilayers on Bi$_2$Te$_3$
We report the formation of Bi(111) bilayer (BL) islands and crater structures on Bi$_2$Te$_3$(111) surfaces induced by voltage pulses from an STM tip. Pulses above a threshold voltage ($+3$ V) produce craters $\sim 0.5$ microns in diameter, similar to the size of the tip. Redeposited material self-assembles into a network of atomically ordered islands with a lattice constant identical to the underlying Bi$_2$Te$_3$ surface. The island size monotonically decreases over several microns from the p…

Best-of-L: Cross-Lingual Reward Modeling for Mathematical Reasoning
Sara Rajaee, Rochelle Choenni, Ekaterina Shutova, Christof Monz
https://arxiv.org/abs/2509.15811 https://

Best-of-L: Cross-Lingual Reward Modeling for Mathematical Reasoning
While the reasoning abilities of large language models (LLMs) continue to advance, it remains unclear how such ability varies across languages in multilingual LLMs and whether different languages produce reasoning paths that complement each other. To investigate this question, we train a reward model to rank generated responses for a given question across languages. Our results show that our cross-lingual reward model substantially improves mathematical reasoning performance compared to using r…

Warm, water-depleted rocky exoplanets with surface ionic liquids - a proposed class for planetary #habitability: https://www.pnas.org/doi/10.1073/pnas.2425520122 -> Planets without water could still produce certain liquids, a new study finds: https://news.mit.edu/2025/planets-without-water-could-still-produce-certain-liquids-0811 - lab experiments show “ionic liquids” can form through common planetary processes and might be capable of supporting life even on waterless planets.

Investigating Training Data Detection in AI Coders
Tianlin Li, Yunxiang Wei, Zhiming Li, Aishan Liu, Qing Guo, Xianglong Liu, Dongning Sun, Yang Liu
https://arxiv.org/abs/2507.17389

Investigating Training Data Detection in AI Coders
Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these models occasionally produce outputs that contain proprietary or sensitive code snippets, raising concerns about potential non-compliant use of training data, and posing risks to privacy and intellectual property. To ensure responsible and compliant deployment of CodeLLMs, training data detection (TDD) has become a critical task. While recent TDD methods have…

Revealed and Concealed Repression: Measurement, Deterrence, and Backlash
Maria Titova, Emily Hencken Ritter, Mehdi Shadmehr
https://arxiv.org/abs/2507.16997 https://

Revealed and Concealed Repression: Measurement, Deterrence, and Backlash
Regimes routinely conceal acts of repression. We show that observed repression may be negatively correlated with total repression -- which includes both revealed and concealed acts -- across time and space. This distortion implies that policy interventions aimed at reducing repression by incentivizing regimes can produce perverse effects. It also poses challenges for research evaluating the efficacy of repression -- its deterrent and backlash effects. To address this, we develop a model in whic…

Distribution Estimation for Global Data Association via Approximate Bayesian Inference
Yixuan Jia, Mason B. Peterson, Qingyuan Li, Yulun Tian, Jonathan P. How
https://arxiv.org/abs/2509.15565

Distribution Estimation for Global Data Association via Approximate Bayesian Inference
Global data association is an essential prerequisite for robot operation in environments seen at different times or by different robots. Repetitive or symmetric data creates significant challenges for existing methods, which typically rely on maximum likelihood estimation or maximum consensus to produce a single set of associations. However, in ambiguous scenarios, the distribution of solutions to global data association problems is often highly multimodal, and such single-solution approaches f…

Trump administration escalates purge of senior US intelligence officials, Economist reports: https://benborges.xyz/2025/08/22/trump-administration-escalates-purge-of.html

A Deep-Learning-Driven Optimization-Based Inverse Solver for Accelerating the Marchenko Method
Ning Wang, Tariq Alkhalifah
https://arxiv.org/abs/2509.16774 https://

A Deep-Learning-Driven Optimization-Based Inverse Solver for Accelerating the Marchenko Method
The Marchenko method is a powerful tool for reconstructing full-wavefield Green's functions using surface-recorded seismic data. These Green's functions can then be utilized to produce subsurface images that are not affected by artifacts caused by internal multiples. Despite its advantages, the method is computationally demanding, primarily due to the iterative nature of estimating the focusing functions, which links the Green's functions to the surface reflection response. To address this limi…

Spintronic Bayesian Hardware Driven by Stochastic Magnetic Domain Wall Dynamics
Tianyi Wang, Bingqian Dai, Kin Wong, Yaochen Li, Yang Cheng, Qingyuan Shu, Haoran He, Puyang Huang, Hanshen Huang, Kang L. Wang
https://arxiv.org/abs/2507.17193

Spintronic Bayesian Hardware Driven by Stochastic Magnetic Domain Wall Dynamics
As artificial intelligence (AI) advances into diverse applications, ensuring reliability of AI models is increasingly critical. Conventional neural networks offer strong predictive capabilities but produce deterministic outputs without inherent uncertainty estimation, limiting their reliability in safety-critical domains. Probabilistic neural networks (PNNs), which introduce randomness, have emerged as a powerful approach for enabling intrinsic uncertainty quantification. However, traditional C…

AI Knows Best? The Paradox of Expertise, AI-Reliance, and Performance in Educational Tutoring Decision-Making Tasks
Eason Chen, Jeffrey Li, Scarlett Huang, Xinyi Tang, Jionghao Lin, Paulo Carvalho, Kenneth Koedinger
https://arxiv.org/abs/2509.16772

AI Knows Best? The Paradox of Expertise, AI-Reliance, and Performance in Educational Tutoring Decision-Making Tasks
We present an empirical study of how both experienced tutors and non-tutors judge the correctness of tutor praise responses under different Artificial Intelligence (AI)-assisted interfaces, types of explanation (textual explanations vs. inline highlighting). We first fine-tuned several Large Language Models (LLMs) to produce binary correctness labels and explanations, achieving up to 88% accuracy and 0.92 F1 score with GPT-4. We then let the GPT-4 models assist 95 participants in tutoring decis…

Spin versus Magic: Lessons from Gluon and Graviton Scattering
John Gargalionis, Nathan Moynihan, Sokratis Trifinopoulos, Ewan N. V. Wallace, Chris D. White, Martin J. White
https://arxiv.org/abs/2508.14967

Spin versus Magic: Lessons from Gluon and Graviton Scattering
The quantum property of non-stabiliserness, also known as magic, plays a key role in designing quantum computing systems. How to produce, manipulate and enhance magic remains mysterious, such that concrete examples of physical systems that manifest magic behaviour are sought after. In this paper, we study two-particle scattering of gluons and gravitons in Yang--Mills theory and General Relativity, as well as their supersymmetric extensions. This provides an interesting case of two-qubit systems…

Just heard chef Luke Holder say “we have this saying: less time cooking it, more time sourcing it. Trying to find the right type of produce because we’re only middlemen between great producers and great guests.”
I’m gonna be chewing on that for a while, I think.

How Large Language Models are Designed to Hallucinate
Richard Ackermann, Simeon Emanuilov
https://arxiv.org/abs/2509.16297 https://arxiv.org/pdf/2509.16297…

How Large Language Models are Designed to Hallucinate
Large language models (LLMs) achieve remarkable fluency across linguistic and reasoning tasks but remain systematically prone to hallucination. Prevailing accounts attribute hallucinations to data gaps, limited context, or optimization errors. We argue instead that hallucination is a structural outcome of the transformer architecture. As coherence engines, transformers are compelled to produce fluent continuations, with self-attention simulating the relational structure of meaning but lacking t…

In Italy, for thirty years under the Borgias, they had warfare, terror,
murder, and bloodshed, but they produced Michaelangelo, Leonardo da Vinci
and the Renaissance. In Switzerland, they had brotherly love, they had
five hundred years of democracy and peace -- and what did they produce?
The cuckoo-clock.
-- Orson Welles, "The Third Man"

Reverse Engineering of Music Mixing Graphs with Differentiable Processors and Iterative Pruning
Sungho Lee, Marco Mart\'inez-Ram\'irez, Wei-Hsiang Liao, Stefan Uhlich, Giorgio Fabbro, Kyogu Lee, Yuki Mitsufuji
https://arxiv.org/abs/2509.15948

Reverse Engineering of Music Mixing Graphs with Differentiable Processors and Iterative Pruning
Reverse engineering of music mixes aims to uncover how dry source signals are processed and combined to produce a final mix. We extend the prior works to reflect the compositional nature of mixing and search for a graph of audio processors. First, we construct a mixing console, applying all available processors to every track and subgroup. With differentiable processor implementations, we optimize their parameters with gradient descent. Then, we repeat the process of removing negligible process…

$r$-process Heating Feedback on Disk Outflows from Neutron Star Mergers
Li-Ting Ma, Kuo-Chuan Pan, Meng-Ru Wu, Rodrigo Fern\'andez
https://arxiv.org/abs/2508.15288 https://

$r$-process Heating Feedback on Disk Outflows from Neutron Star Mergers
Neutron star mergers produce $r$-process elements, with yields that are sensitive to the kinematic and thermodynamic properties of the ejecta. These ejecta properties are potentially affected by dynamically-important feedback from $r$-process heating, which is usually not coupled to the hydrodynamics in post-merger simulations modeling the ejecta launching and expansion. The multi-messenger detection of GW170817 showed the importance of producing reliable ejecta predictions, to maximize the dia…

Discovery of SiC and Iron Dust Around AGB Stars in the very Metal-Poor Sextans A Dwarf Galaxy with JWST: Implications for Dust Production at High Redshift
M. L. Boyer, G. C. Sloan, A. Nanni, E. Tarantino, I. McDonald, S. Goldman, J. A. D. L Blommaert, F. Dell'Agli, M. Di Criscienzo, D. A. Garcia-Hernandez, R. D. Gehrz, M. A. T. Groenewegen, A. Javadi, O. C. Jones, F. Kemper, M. Marengo, K. B. W. McQuinn, J. M. Oliveira, G. Pastorelli, J. Roman-Duval, R. Sahai, E. D. Skillman, S. Sr…

Discovery of SiC and Iron Dust Around AGB Stars in the very Metal-Poor Sextans A Dwarf Galaxy with JWST: Implications for Dust Production at High Redshift
Low-resolution infrared spectroscopy from JWST confirms the presence of SiC and likely metallic iron dust around asymptotic giant branch (AGB) stars in the Sextans A dwarf galaxy, which has a metallicity ~1%-7% Z_sun. While metal-poor carbon-rich AGB stars are known to produce copious amounts of amorphous carbon dust owing to the dredge up of newly synthesized carbon, this is the first time that Si- and Fe-bearing dust has been detected at this extreme metallicity. Of the six AGB stars observed…

Predict, Reposition, and Allocate: A Greedy and Flow-Based Architecture for Sustainable Urban Food Delivery
Aqsa Ashraf Makhdomi, Iqra Altaf Gillani
https://arxiv.org/abs/2507.15282

Predict, Reposition, and Allocate: A Greedy and Flow-Based Architecture for Sustainable Urban Food Delivery
The rapid proliferation of food delivery platforms has reshaped urban mobility but has also contributed significantly to environmental degradation through increased greenhouse gas emissions. Existing optimization mechanisms produce sub-optimal outcomes as they do not consider environmental sustainability their optimization objective. This study proposes a novel eco-friendly food delivery optimization framework that integrates demand prediction, delivery person routing, and order allocation to m…

RadReason: Radiology Report Evaluation Metric with Reasons and Sub-Scores
Yingshu Li, Yunyi Liu, Lingqiao Liu, Lei Wang, Luping Zhou
https://arxiv.org/abs/2508.15464 https://

RadReason: Radiology Report Evaluation Metric with Reasons and Sub-Scores
Evaluating automatically generated radiology reports remains a fundamental challenge due to the lack of clinically grounded, interpretable, and fine-grained metrics. Existing methods either produce coarse overall scores or rely on opaque black-box models, limiting their usefulness in real-world clinical workflows. We introduce RadReason, a novel evaluation framework for radiology reports that not only outputs fine-grained sub-scores across six clinically defined error types, but also produces h…

SABER: Uncovering Vulnerabilities in Safety Alignment via Cross-Layer Residual Connection
Maithili Joshi, Palash Nandi, Tanmoy Chakraborty
https://arxiv.org/abs/2509.16060 https…

SABER: Uncovering Vulnerabilities in Safety Alignment via Cross-Layer Residual Connection
Large Language Models (LLMs) with safe-alignment training are powerful instruments with robust language comprehension capabilities. These models typically undergo meticulous alignment procedures involving human feedback to ensure the acceptance of safe inputs while rejecting harmful or unsafe ones. However, despite their massive scale and alignment efforts, LLMs remain vulnerable to jailbreak attacks, where malicious users manipulate the model to produce harmful outputs that it was explicitly t…

Model-robust standardization in stepped wedge designs
Xi Fang, Xueqi Wang, Patrick J. Heagerty, Bingkai Wang, Fan Li
https://arxiv.org/abs/2507.17190 https://

Model-robust standardization in stepped wedge designs
Stepped-wedge cluster-randomized trials (SW-CRTs) are widely used in healthcare and implementation science, providing an ethical advantage by ensuring all clusters eventually receive the intervention. The staggered rollout of treatment introduces complexities in defining and estimating treatment effect estimands, particularly under informative sizes. Traditional model-based methods, including generalized estimating equations (GEE) and linear mixed models (LMM), produce estimates that depend on …

Considering contact forces during the formation of planetesimals by gravitational collapse: mutual orbits, spin states, and shapes
Jackson T. Barnes, Stephen R. Schwartz, Seth A. Jacobson
https://arxiv.org/abs/2507.16739

Considering contact forces during the formation of planetesimals by gravitational collapse: mutual orbits, spin states, and shapes
In this work, we apply a soft-sphere discrete element method (SSDEM) within the PKDGRAV N-body integrator to investigate the formation of planetesimal systems through the gravitational collapse of clouds of super-particles. Previously published numerical models have demonstrated that the gravitational collapse of pebble clouds is an efficient pathway to produce binary planetesimal systems. However, such investigations were limited by their use of a perfect-merger and inflated-radii super-partic…

LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning
Jelle Luijkx, Runyu Ma, Zlatan Ajanovi\'c, Jens Kober
https://arxiv.org/abs/2509.16615 https://…

LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning
Reinforcement learning (RL) is a promising approach for robotic manipulation, but it can suffer from low sample efficiency and requires extensive exploration of large state-action spaces. Recent methods leverage the commonsense knowledge and reasoning abilities of large language models (LLMs) to guide exploration toward more meaningful states. However, LLMs can produce plans that are semantically plausible yet physically infeasible, yielding unreliable behavior. We introduce LLM-TALE, a framewo…

VulCoCo: A Simple Yet Effective Method for Detecting Vulnerable Code Clones
Tan Bui, Yan Naing Tun, Thanh Phuc Nguyen, Yindu Su, Ferdian Thung, Yikun Li, Han Wei Ang, Yide Yin, Frank Liauw, Lwin Khin Shar, Eng Lieh Ouh, Ting Zhang, David Lo
https://arxiv.org/abs/2507.16661

VulCoCo: A Simple Yet Effective Method for Detecting Vulnerable Code Clones
Code reuse is common in modern software development, but it can also spread vulnerabilities when developers unknowingly copy risky code. The code fragments that preserve the logic of known vulnerabilities are known as vulnerable code clones (VCCs). Detecting those VCCs is a critical but challenging task. Existing VCC detection tools often rely on syntactic similarity or produce coarse vulnerability predictions without clear explanations, limiting their practical utility. In this paper, we propo…

Parametric Integration with Neural Integral Operators
Christoph Schied, Alexander Keller
https://arxiv.org/abs/2507.17440 https://arx…

Parametric Integration with Neural Integral Operators
Real-time rendering imposes strict limitations on the sampling budget for light transport simulation, often resulting in noisy images. However, denoisers have demonstrated that it is possible to produce noise-free images through filtering. We enhance image quality by removing noise before material shading, rather than filtering already shaded noisy images. This approach allows for material-agnostic denoising (MAD) and leverages machine learning by approximating the light transport integral oper…

Tinker: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene Optimization
Canyu Zhao, Xiaoman Li, Tianjian Feng, Zhiyue Zhao, Hao Chen, Chunhua Shen
https://arxiv.org/abs/2508.14811

Tinker: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene Optimization
We introduce Tinker, a versatile framework for high-fidelity 3D editing that operates in both one-shot and few-shot regimes without any per-scene finetuning. Unlike prior techniques that demand extensive per-scene optimization to ensure multi-view consistency or to produce dozens of consistent edited input views, Tinker delivers robust, multi-view consistent edits from as few as one or two images. This capability stems from repurposing pretrained diffusion models, which unlocks their latent 3D …

See it. Say it. Sorted: Agentic System for Compositional Diagram Generation
Hantao Zhang, Jingyang Liu, Ed Li
https://arxiv.org/abs/2508.15222 https://arxi…

See it. Say it. Sorted: Agentic System for Compositional Diagram Generation
We study sketch-to-diagram generation: converting rough hand sketches into precise, compositional diagrams. Diffusion models excel at photorealism but struggle with the spatial precision, alignment, and symbolic structure required for flowcharts. We introduce See it. Say it. Sorted., a training-free agentic system that couples a Vision-Language Model (VLM) with Large Language Models (LLMs) to produce editable Scalable Vector Graphics (SVG) programs. The system runs an iterative loop in which a …

D-REX: A Benchmark for Detecting Deceptive Reasoning in Large Language Models
Satyapriya Krishna, Andy Zou, Rahul Gupta, Eliot Krzysztof Jones, Nick Winter, Dan Hendrycks, J. Zico Kolter, Matt Fredrikson, Spyros Matsoukas
https://arxiv.org/abs/2509.17938

D-REX: A Benchmark for Detecting Deceptive Reasoning in Large Language Models
The safety and alignment of Large Language Models (LLMs) are critical for their responsible deployment. Current evaluation methods predominantly focus on identifying and preventing overtly harmful outputs. However, they often fail to address a more insidious failure mode: models that produce benign-appearing outputs while operating on malicious or deceptive internal reasoning. This vulnerability, often triggered by sophisticated system prompt injections, allows models to bypass conventional saf…

All incompatible sets of measurements can generate Buscemi nonlocality
Andr\'es F. Ducuara, Patryk Lipka-Bartosik, Cristian E. Susa, Paul Skrzypczyk
https://arxiv.org/abs/2508.14421

All incompatible sets of measurements can generate Buscemi nonlocality
The presence of Bell-nonlocality in the correlations arising from measuring spatially-separated systems guarantees that the sets of measurements used are necessarily incompatible. Not all sets of incompatible measurements can however lead to Bell-nonlocality, as there exist incompatible sets of measurements which can only produce local correlations. In this work we prove that all sets of incompatible measurements are nevertheless able to generate nonlocality in an extended Bell scenario where q…

Instability of inverse probability weighting methods and a remedy for non-ignorable missing data
Pengfei Li, Jing Qin, Yukun Liu
https://arxiv.org/abs/2507.17137 https://…

Instability of inverse probability weighting methods and a remedy for non-ignorable missing data
Inverse probability weighting (IPW) methods are commonly used to analyze non-ignorable missing data under the assumption of a logistic model for the missingness probability. However, solving IPW equations numerically may involve non-convergence problems when the sample size is moderate and the missingness probability is high. Moreover, those equations often have multiple roots, and identifying the best root is challenging. Therefore, IPW methods may have low efficiency or even produce biased re…

VeriOpt: PPA-Aware High-Quality Verilog Generation via Multi-Role LLMs
Kimia Tasnia, Alexander Garcia, Tasnuva Farheen, Sazadur Rahman
https://arxiv.org/abs/2507.14776

VeriOpt: PPA-Aware High-Quality Verilog Generation via Multi-Role LLMs
The rapid adoption of large language models(LLMs) in hardware design has primarily focused on generating functionally correct Verilog code, overlooking critical Power Performance-Area(PPA) metrics essential for industrial-grade designs. To bridge this gap, we propose VeriOpt, a novel framework that leverages role-based prompting and PPA-aware optimization to enable LLMs to produce high-quality, synthesizable Verilog. VeriOpt structures LLM interactions into specialized roles (e.g., Planner, Pro…

Think, Verbalize, then Speak: Bridging Complex Thoughts and Comprehensible Speech
Sang Hoon Woo, Sehun Lee, Kang-wook Kim, Gunhee Kim
https://arxiv.org/abs/2509.16028 https://…

Think, Verbalize, then Speak: Bridging Complex Thoughts and Comprehensible Speech
Spoken dialogue systems increasingly employ large language models (LLMs) to leverage their advanced reasoning capabilities. However, direct application of LLMs in spoken communication often yield suboptimal results due to mismatches between optimal textual and verbal delivery. While existing approaches adapt LLMs to produce speech-friendly outputs, their impact on reasoning performance remains underexplored. In this work, we propose Think-Verbalize-Speak, a framework that decouples reasoning fr…

Wavelength Requirements for Life Detection via Reflected Light Spectroscopy of Rocky Exoplanets
Joshua Krissansen-Totton, Anna Grace Ulses, Maxwell Frissell, Samantha Gilbert-Janizek, Amber Young, Jacob Lustig-Yaeger, Tyler Robinson, Stephanie Olson, Eleonora Alei, Giada Arney, Celeste Hagee, Chester Harman, Natalie Hinkel, Emilie Lafleche, Natasha Latouf, Avi Mandell, Mark M. Moussa, Niki Parenteau, Sukrit Ranjan, Blair Russell, Edward W. Schwieterman, Clara Sousa-Silva, Armen Tokadji…

Wavelength Requirements for Life Detection via Reflected Light Spectroscopy of Rocky Exoplanets
Searching for signs of life is a primary goal of the Habitable Worlds Observatory (HWO). However, merely detecting oxygen, methane, or other widely discussed biosignatures is insufficient evidence for a biosphere. In parallel with biosignature detection, exoplanet life detection additionally requires characterization of the broader physicochemical context to evaluate planetary habitability and the plausibility that life could produce a particular biosignature in a given environment. Life detect…

Model Simplification through refinement
Dmitry Brodsky, Benjamin Watson
https://arxiv.org/abs/2507.15186 https://arxiv.org/pdf/2507.1…

Model Simplification through refinement
As modeling and visualization applications proliferate, there arises a need to simplify large polygonal models at interactive rates. Unfortunately existing polygon mesh simplification algorithms are not well suited for this task because they are either too slow (requiring the simplified model to be pre-computed) or produce models that are too poor in quality. These shortcomings become particularly acute when models are extremely large. We present an algorithm suitable for simplification of larg…

Filtered Instantons and the Concordance of Satellites
Ivan So
https://arxiv.org/abs/2507.14350 https://arxiv.org/pdf/2507.14350

Filtered Instantons and the Concordance of Satellites
In \cite{NST23}, Nozaki-Sato-Taniguchi defined a family of invariants $ r_s $ for integer homology spheres with filtered instanton homology \cite{FS92}. Coupling these with techniques in classical knot theory, we produce some results in the knot concordance group, including criteria for a family of satellite knots to be linearly independent and the independence of what we call the Whitehead $ n $-ble $ P_n $.

Dr. Boot: Bootstrapping Program Synthesis Language Models to Perform Repairing
Noah van der Vleuten
https://arxiv.org/abs/2507.15889 https://

Dr. Boot: Bootstrapping Program Synthesis Language Models to Perform Repairing
Language models for program synthesis are usually trained and evaluated on programming competition datasets (MBPP, APPS). However, these datasets are limited in size and quality, while these language models are extremely data hungry. Additionally, the language models have a misaligned program synthesis process compared to humans. While humans iteratively develop code with the help of a compiler, most program synthesis models currently produce code in one go. To solve these issues, we introduce …

Austin-based Aalo Atomics, which is building a modular nuclear reactor and data center, set to finish construction in 2026, raised a $100M Series B led by Valor (Julia Hornstein/Business Insider)
https://www.businessinsider.com/aalo-atomi

Aalo Atomics lands $100 million to launch nuclear reactors to power AI
Aalo Atomics raises $100 million to mass-produce nuclear reactors to power data centers amid the growing energy demand from AI.

Investigating Bias: A Multilingual Pipeline for Generating, Solving, and Evaluating Math Problems with LLMs
Mariam Mahran, Katharina Simbeck
https://arxiv.org/abs/2509.17701 htt…

Investigating Bias: A Multilingual Pipeline for Generating, Solving, and Evaluating Math Problems with LLMs
Large Language Models (LLMs) are increasingly used for educational support, yet their response quality varies depending on the language of interaction. This paper presents an automated multilingual pipeline for generating, solving, and evaluating math problems aligned with the German K-10 curriculum. We generated 628 math exercises and translated them into English, German, and Arabic. Three commercial LLMs (GPT-4o-mini, Gemini 2.5 Flash, and Qwen-plus) were prompted to produce step-by-step solu…

SAGA: Learning Signal-Aligned Distributions for Improved Text-to-Image Generation
Paul Grimal, Micha\"el Soumm, Herv\'e Le Borgne, Olivier Ferret, Akihiro Sugimoto
https://arxiv.org/abs/2508.13866

SAGA: Learning Signal-Aligned Distributions for Improved Text-to-Image Generation
State-of-the-art text-to-image models produce visually impressive results but often struggle with precise alignment to text prompts, leading to missing critical elements or unintended blending of distinct concepts. We propose a novel approach that learns a high-success-rate distribution conditioned on a target prompt, ensuring that generated images faithfully reflect the corresponding prompts. Our method explicitly models the signal component during the denoising process, offering fine-grained …

Russia wants to produce its new Su-57 fighter jets in India: https://benborges.xyz/2025/09/02/russia-wants-to-produce-its.html

Beyond Video-to-SFX: Video to Audio Synthesis with Environmentally Aware Speech
Xinlei Niu, Jianbo Ma, Dylan Harper-Harris, Xiangyu Zhang, Charles Patrick Martin, Jing Zhang
https://arxiv.org/abs/2509.15492

Beyond Video-to-SFX: Video to Audio Synthesis with Environmentally Aware Speech
The generation of realistic, context-aware audio is important in real-world applications such as video game development. While existing video-to-audio (V2A) methods mainly focus on Foley sound generation, they struggle to produce intelligible speech. Meanwhile, current environmental speech synthesis approaches remain text-driven and fail to temporally align with dynamic video content. In this paper, we propose Beyond Video-to-SFX (BVS), a method to generate synchronized audio with environmental…

SoftBank buys Foxconn's Ohio EV plant; Foxconn will produce AI servers at the plant as part of Softbank's $500B Stargate project with OpenAI and Oracle (Debby Wu/Bloomberg)
https://www.bloomberg.com/news/articles/2025-0…

Hadrian, which is building largely automated factories to produce space and defense parts, raised a $260M Series C, bringing its total funding to ~$500M (Aria Alamalhodaei/TechCrunch)
https://techcrunch.com/2025/07/17/hadria…

Hadrian raises $260M to build out automated factories for space and defense parts | TechCrunch
Hadrian wants to revolutionize American manufacturing through automation.