Tootfinder

Good discussion of Apple's AI paper ((without denying that GenAI can' t think or reason and produce bullshit)
#AI

Imagine you want to produce E-Fuels⚡⛽ but the power company does not want to sell you electricity⚡
That appears to be what potential E-Fuels producers faced in Iceland🇮🇸. The country uses 100% renewable electricity (hydro/geo) & could produce more.
Yet, Iceland's electricity producer Landsvirkjun does not have enough electricity⚡. Building new plants is delayed by slow permitting 📝. Landsvirkjun has therefore set out priorities.

Iceland's E-Fuels Controversy
Hydrogen and E-Fuels companies want to utilize Iceland's abundant renewable energy sources. But Iceland's largest energy company Landsvirkjun does not want to sell electricity to them. E-Fuels producers hope that European authorities will intervene, the EFTA Surveillane Authority investigates.

🌳 InventWood is about to mass produce wood that’s stronger than steel
https://techcrunch.com/2025/05/12/inventwood-is-about-to-mass-produce-wood-thats-stronger-than-steel/

Exclusive: InventWood is about to mass-produce wood that’s stronger than steel | TechCrunch
The material has 50% more tensile strength than steel with a strength-to-weight ratio that’s ten-times better.

Urban Discoveries II 🌆
都市发现 II 🌆
📷 Pentax MX
🎞️Lucky SHD 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Yiding Cao Geld mit PayPal.Me senden
Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

BugGen: A Self-Correcting Multi-Agent LLM Pipeline for Realistic RTL Bug Synthesis
Surya Jasper, Minh Luu, Evan Pan, Aakash Tyagi, Michael Quinn, Jiang Hu, David Kebo Houngninou
https://arxiv.org/abs/2506.10501

BugGen: A Self-Correcting Multi-Agent LLM Pipeline for Realistic RTL Bug Synthesis
Hardware complexity continues to strain verification resources, motivating the adoption of machine learning (ML) methods to improve debug efficiency. However, ML-assisted debugging critically depends on diverse and scalable bug datasets, which existing manual or automated bug insertion methods fail to reliably produce. We introduce BugGen, a first of its kind, fully autonomous, multi-agent pipeline leveraging Large Language Models (LLMs) to systematically generate, insert, and validate realisti…

Very excited about this! Code to access GRIN will help lots of Google Books partners, and the example might open other doors, as well as the obvious benefits of access to data!
'Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability' https://arxiv.org/abs/2506…

Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability
Large language models (LLMs) use data to learn about the world in order to produce meaningful correlations and predictions. As such, the nature, scale, quality, and diversity of the datasets used to train these models, or to support their work at inference time, have a direct impact on their quality. The rapid development and adoption of LLMs of varying quality has brought into focus the scarcity of publicly available, high-quality training data and revealed an urgent need to ground the steward…

On a few pitfalls in KL divergence gradient estimation for RL
Yunhao Tang, R\'emi Munos
https://arxiv.org/abs/2506.09477 https://…

On a few pitfalls in KL divergence gradient estimation for RL
We point out a few pitfalls in implementing gradient estimation for KL divergence in RL training for LLM, as seen in a number of open source projects and papers. The first major pitfall is to differentiate through the KL estimate as loss functions to minimize KL divergence. We show that such implementations are generally incorrect and do not produce the desired KL gradient. Secondly, we show that some implementations do not account for the sequential nature of the estimation problem and produce…

Robust copula estimation for one-shot devices with correlated failure modes
E. Castilla, P. J. Chocano
https://arxiv.org/abs/2506.10152 https://

Robust copula estimation for one-shot devices with correlated failure modes
This paper presents a robust method for estimating copula models to evaluate dependence between failure modes in one-shot devices-systems designed for single use and destroyed upon activation. Traditional approaches, such as maximum likelihood estimation (MLE), often produce unreliable results when faced with outliers or model misspecification. To overcome these limitations, we introduce a divergence-based estimation technique that enhances robustness and provides a more reliable characterizati…

Step-by-step Instructions and a Simple Tabular Output Format Improve the Dependency Parsing Accuracy of LLMs
Hiroshi Matsuda, Chunpeng Ma, Masayuki Asahara
https://arxiv.org/abs/2506.09983

Step-by-step Instructions and a Simple Tabular Output Format Improve the Dependency Parsing Accuracy of LLMs
Recent advances in large language models (LLMs) have enabled impressive performance in various tasks. However, standard prompting often struggles to produce structurally valid and accurate outputs, especially in dependency parsing. We propose a novel step-by-step instruction strategy, where universal part-of-speech tagging precedes the prediction of syntactic heads and dependency labels, and a simplified CoNLL-U like output format, our method achieves state-of-the-art accuracy on Universal Depe…

Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds
Vahan Arsenyan, Elen Vardanyan, Arnak Dalalyan
https://arxiv.org/abs/2506.09681

Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds
Generative modeling aims to produce new random examples from an unknown target distribution, given access to a finite collection of examples. Among the leading approaches, denoising diffusion probabilistic models (DDPMs) construct such examples by mapping a Brownian motion via a diffusion process driven by an estimated score function. In this work, we first provide empirical evidence that DDPMs are robust to constant-variance noise in the score evaluations. We then establish finite-sample guara…

Predictive control of wastewater treatment plants as energy-autonomous water resource recovery facilities
Otacilio B. L. Neto, Michela Mulas, Iiro Harjunkoski, Francesco Corona
https://arxiv.org/abs/2506.10490

Predictive control of wastewater treatment plants as energy-autonomous water resource recovery facilities
This work proposes an automatic control solution for the operation of conventional wastewater treatment plants (WWTPs) as energy-autonomous water resource recovery facilities. We first conceptualize a classification of the quality of treated water for three resource recovery applications (environmental, industrial, and agricultural water reuse). We then present an output-feedback model predictive controller (Output MPC) that operates a plant to produce water of specific quality class, while als…

From Intention to Execution: Probing the Generalization Boundaries of Vision-Language-Action Models
Irving Fang, Juexiao Zhang, Shengbang Tong, Chen Feng
https://arxiv.org/abs/2506.09930

From Intention to Execution: Probing the Generalization Boundaries of Vision-Language-Action Models
One promise that Vision-Language-Action (VLA) models hold over traditional imitation learning for robotics is to leverage the broad generalization capabilities of large Vision-Language Models (VLMs) to produce versatile, "generalist" robot policies. However, current evaluations of VLAs remain insufficient. Traditional imitation learning benchmarks are unsuitable due to the lack of language instructions. Emerging benchmarks for VLAs that incorporate language often come with limited evaluation ta…

What is the Cost of Differential Privacy for Deep Learning-Based Trajectory Generation?
Erik Buchholz, Natasha Fernandes, David D. Nguyen, Alsharif Abuadbba, Surya Nepal, Salil S. Kanhere
https://arxiv.org/abs/2506.09312

What is the Cost of Differential Privacy for Deep Learning-Based Trajectory Generation?
While location trajectories offer valuable insights, they also reveal sensitive personal information. Differential Privacy (DP) offers formal protection, but achieving a favourable utility-privacy trade-off remains challenging. Recent works explore deep learning-based generative models to produce synthetic trajectories. However, current models lack formal privacy guarantees and rely on conditional information derived from real data during generation. This work investigates the utility cost of e…

I wonder if AI’s effectiveness will speed up the inevitable death of some ecosystems.
If folks want the “best” (and I mean least shit) Agentic AI experience, they will probably gravitate towards more populated communities where the training data can produce a semblance of “working”.
This will likely flat-line some communities since many devs want something that works.

🇺🇦 #NowPlaying on #BBC6Music's #DonLettsCultureClashRadio
Fat Produce:
🎵 No Way
#FatProduce
https://fatproduce.bandcamp.com/album/no-way-54-46-was-my-number
https://open.spotify.com/track/655GfEtxXoADMMYxM0ZScy

Does Residuals-on-Residuals Regression Produce Representative Estimates of Causal Effects?
Apoorva Lal, Winston Chou
https://arxiv.org/abs/2506.07462 https…

Does Residuals-on-Residuals Regression Produce Representative Estimates of Causal Effects?
Double Machine Learning is commonly used to estimate causal effects in large observational datasets. The "residuals-on-residuals" regression estimator (RORR) is especially popular for its simplicity and computational tractability. However, when treatment effects are heterogeneous, the proper interpretation of RORR may not be well understood. We show that, for many-valued treatments with continuous dose-response functions, RORR converges to a conditional variance-weighted average of derivatives …

TTrace: Lightweight Error Checking and Diagnosis for Distributed Training
Haitian Jiang, Shaowei Zhu, Zhen Zhang, Zhenyu Song, Xinwei Fu, Zhen Jia, Yida Wang, Jinyang Li
https://arxiv.org/abs/2506.09280

TTrace: Lightweight Error Checking and Diagnosis for Distributed Training
Distributed training is essential for scaling the training of large neural network models, such as large language models (LLMs), across thousands of GPUs. However, the complexity of distributed training programs makes them particularly prone to silent bugs, which do not produce explicit error signal but lead to incorrect training outcome. Effectively detecting and localizing such silent bugs in distributed training is challenging. Common debugging practice using metrics like training loss or gr…

Plants produce more nectar when they ‘hear’ bees buzzing, scientists find;
Researchers suggest buzzing noises could be used as environmentally friendly way to enhance crop pollination
https://www.theguardian.com/environment/20

"Ocean currents can generate electricity, and our study shows Africa's seas have some of the strongest"
#Africa #Oceans #Energy

Ocean currents can generate electricity, and our study shows Africa's seas have some of the strongest
The world's oceans cover more than 70% of Earth's surface. They're filled with currents, some much stronger than the fastest flowing large rivers. These currents can be harnessed as clean, marine renewable energy. Marine energy is much more predictable and reliable than many other forms of renewable energy because unlike the sun and wind, which regularly do not produce electricity, ocean currents never stop moving around the planet. New research has found that the eastern and south-eastern coas…

Distinguishing Monochromatic Signals in LISA and Taiji: Ultralight Dark Matter versus Gravitational Waves
Heng-Tao Xu, Yue-Hui Yao, Yong Tang, Yue-Liang Wu
https://arxiv.org/abs/2506.09744

Distinguishing Monochromatic Signals in LISA and Taiji: Ultralight Dark Matter versus Gravitational Waves
Ultralight dark matter (ULDM) is an attractive candidate for cold dark matter, one of the main mysterious components of the Universe. Recent studies suggest that gravitational-wave (GW) laser interferometers can also detect bosonic ULDM fields, which would produce monochromatic signals resembling those from gravitational waves (GWs). Distinguishing between these potential origins therefore would be essential. In this work, we develop a method to address this challenge for space-based GW interfe…

Exploiting Control-flow Enforcement Technology for Sound and Precise Static Binary Disassembly
Brian Zhao, Yiwei Yang, Yusheng Zheng, Andi Quinn
https://arxiv.org/abs/2506.09426

Exploiting Control-flow Enforcement Technology for Sound and Precise Static Binary Disassembly
Rewriting x86_64 binaries-whether for security hardening, dynamic instrumentation, or performance profiling is notoriously difficult due to variable-length instructions, interleaved code and data, and indirect jumps to arbitrary byte offsets. Existing solutions (e.g., "superset disassembly") ensure soundness but incur significant overhead and produce large rewritten binaries, especially for on-the-fly instrumentation. This paper addresses these challenges by introducing the Time Variance Author…

Urban Discoveries II 🌆
都市发现 II 🌆
📷 Pentax MX
🎞️Lucky SHD 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

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Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

Lambert's problem in orbital dynamics: a self--contained introduction
Lenox Helene Baloglou, Parneet Gill, Tonatiuh S\'anchez-Vizuet
https://arxiv.org/abs/2506.10556

Lambert's problem in orbital dynamics: a self--contained introduction
Lambert's problem is a classical boundary value problem in analytical mechanics. It arises when trying to determine the energy required to place a particle, subject to a central gravitational potential, in a free fall trajectory connecting two given points on a desired travel time. Due to its mathematical beauty and its relevance in aerospace engineering, it has been and remains the object of attention of countless engineers, mathematicians (pure and applied), and physicists seeking to produce …

This https://arxiv.org/abs/2505.24718 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Reinforcing Video Reasoning with Focused Thinking
Recent advancements in reinforcement learning, particularly through Group Relative Policy Optimization (GRPO), have significantly improved multimodal large language models for complex reasoning tasks. However, two critical limitations persist: 1) they often produce unfocused, verbose reasoning chains that obscure salient spatiotemporal cues and 2) binary rewarding fails to account for partially correct answers, resulting in high reward variance and inefficient learning. In this paper, we propos…

AC/DC: LLM-based Audio Comprehension via Dialogue Continuation
Yusuke Fujita, Tomoya Mizumoto, Atsushi Kojima, Lianbo Liu, Yui Sudo
https://arxiv.org/abs/2506.10312

AC/DC: LLM-based Audio Comprehension via Dialogue Continuation
We propose an instruction-following audio comprehension model that leverages the dialogue continuation ability of large language models (LLMs). Instead of directly generating target captions in training data, the proposed method trains a model to produce responses as if the input caption triggered a dialogue. This dialogue continuation training mitigates the caption variation problem. Learning to continue a dialogue effectively captures the caption's meaning beyond its surface-level words. As a…

Learning Chaotic Dynamics with Neuromorphic Network Dynamics
Yinhao Xu, Georg A. Gottwald, Zdenka Kuncic
https://arxiv.org/abs/2506.10773 https://

Learning Chaotic Dynamics with Neuromorphic Network Dynamics
This study investigates how dynamical systems may be learned and modelled with a neuromorphic network which is itself a dynamical system. The neuromorphic network used in this study is based on a complex electrical circuit comprised of memristive elements that produce neuro-synaptic nonlinear responses to input electrical signals. To determine how computation may be performed using the physics of the underlying system, the neuromorphic network was simulated and evaluated on autonomous predictio…

Execution-Aware Program Reduction for WebAssembly via Record and Replay
Doehyun Baek, Daniel Lehmann, Ben L. Titzer, Sukyoung Ryu, Michael Pradel
https://arxiv.org/abs/2506.07834 …

Execution-Aware Program Reduction for WebAssembly via Record and Replay
WebAssembly (Wasm) programs may trigger bugs in their engine implementations. To aid debugging, program reduction techniques try to produce a smaller variant of the input program that still triggers the bug. However, existing execution-unaware program reduction techniques struggle with large and complex Wasm programs, because they rely on static information and apply syntactic transformations, while ignoring the valuable information offered by the input program's execution behavior. We presen…

In this moment when equity & inclusion efforts are being hindered & erased, the DLF Committee on Equity & Inclusion is creating a Zotero library of related resources for the GLAM community. Let us know what topics would be most helpful to you: https://docs.google.com/f…

Bears WR Rome Odunze worked on upper-body strength, ready to make Year 2 leap with Caleb Williams

https://www.cbssports.com/nfl/news/bears-w

Dynamics of Subsurface Flows in Solar Active Regions During the May 2024 Storm
B Lekshmi, Sushanta Tripathy, Kiran Jain, Alexei Pevtsov
https://arxiv.org/abs/2506.08141

Dynamics of Subsurface Flows in Solar Active Regions During the May 2024 Storm
In May 2024, the Sun exhibited intense magnetic activity, marked by numerous high-intensity flares resulting from the interaction and merging of NOAA ARs 13664 and 13668 in the southern hemisphere and AR 13663 in the northern hemisphere. Notably, AR 13664 displayed an extended lifetime, remaining visible after a full solar rotation and continuing to produce significant flaring activity. In this study, we investigate the evolution of sub-photospheric plasma flows associated with these ARs during…

SPBA: Utilizing Speech Large Language Model for Backdoor Attacks on Speech Classification Models
Wenhan Yao, Fen Xiao, Xiarun Chen, Jia Liu, YongQiang He, Weiping Wen
https://arxiv.org/abs/2506.08346

SPBA: Utilizing Speech Large Language Model for Backdoor Attacks on Speech Classification Models
Deep speech classification tasks, including keyword spotting and speaker verification, are vital in speech-based human-computer interaction. Recently, the security of these technologies has been revealed to be susceptible to backdoor attacks. Specifically, attackers use noisy disruption triggers and speech element triggers to produce poisoned speech samples that train models to become vulnerable. However, these methods typically create only a limited number of backdoors due to the inherent cons…

Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models
Shuai Wang, Zhenhua Liu, Jiaheng Wei, Xuanwu Yin, Dong Li, Emad Barsoum
https://arxiv.org/abs/2506.09532

Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models
We present Athena-PRM, a multimodal process reward model (PRM) designed to evaluate the reward score for each step in solving complex reasoning problems. Developing high-performance PRMs typically demands significant time and financial investment, primarily due to the necessity for step-level annotations of reasoning steps. Conventional automated labeling methods, such as Monte Carlo estimation, often produce noisy labels and incur substantial computational costs. To efficiently generate high-q…

Scattering theory on Riemann surfaces I: Schiffer operators, cohomology, and index theorems
Eric Schippers, Wolfgang Staubach
https://arxiv.org/abs/2506.08160

Scattering theory on Riemann surfaces I: Schiffer operators, cohomology, and index theorems
We consider a compact Riemann surface $\mathscr{R}$ with a complex of non-intersecting Jordan curves, whose complement is a pair of Riemann surfaces with boundary, each of which may be possibly disconnected. We investigate conformally invariant integral operators of Schiffer, which act on $L^{2}$ anti-holomorphic one-forms on one of these surfaces with boundary and produce holomorphic one-forms on the disjoint union. These operators arise in potential theory, boundary value problems, approximat…

This https://arxiv.org/abs/2503.15487 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Fast Two-photon Microscopy by Neuroimaging with Oblong Random Acquisition (NORA)
Advances in neural imaging have enabled neuroscientists to study how large neural populations conspire to produce perception, behavior and cognition. Despite many advances in optical methods, there exists a fundamental tradeoff between imaging speed, field of view, and resolution that limits the scope of neural imaging, especially for the raster-scanning multi-photon imaging needed to image deeper into the brain. One approach to overcoming this trade-off is computational imaging: the co-develop…

2-Group Symmetries of 3-dimensional Defect TQFTs and Their Gauging
Nils Carqueville, Benjamin Haake
https://arxiv.org/abs/2506.08178 https://

2-Group Symmetries of 3-dimensional Defect TQFTs and Their Gauging
A large class of symmetries of topological quantum field theories is naturally described by functors into higher categories of topological defects. Here we study 2-group symmetries of 3-dimensional TQFTs. We explain that these symmetries can be gauged to produce new TQFTs iff certain defects satisfy the axioms of orbifold data. In the special case of Reshetikhin-Turaev theories coming from $G$-crossed braided fusion categories $\mathcal C^\times_G$, we show that there are 0- and 1-form symmetri…

This https://arxiv.org/abs/2504.21726 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Notes sur l'application d'Albanese pour les zéro-cycles
For a smooth projective variety X over an arbitrary field k, we discuss the surjectivity of the Albanese map from the Chow group of zero-cycles of degree zero on X to the group of rational points of the Albanese variety of X. Over arithmetic fields, we use Severi-Brauer fibrations to produce examples where the map is not surjective. For varieties X over the complex field, we discuss the question after extension of the complex field to function fields of varieties. This is related to C. Voisin's…

Biotech uses fermentation to produce milk proteins without cows
https://phys.org/news/2025-06-biotech-fermentation-proteins-cows.html

GenAI is the new Offshoring #ai #llm
https://ardalis.com/genai-is-the-new-offshoring/

This https://arxiv.org/abs/2401.16508 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A synthetic approach to detecting $v_1$-periodic families
We provide a simple proof that the unit map from the sphere spectrum to the connective image-of-$J$ spectrum $\mathrm{j}$ is surjective on homotopy groups. This is achieved using a novel $t$-structure on the category of $E$-synthetic spectra and a specific construction of $\mathbf{F}_p$- and BP-synthetic lifts of $\mathrm{j}$. These synthetic lifts then easily produce modified Adams and Adams--Novikov spectral sequences for $\mathrm{j}$ which we use the prove the above detection statement, all …

Extracting Information About Publication Venues Using Citation-Informed Transformers
Brian D. Zimmerman, Joshua Folkins, Olga Vechtomova
https://arxiv.org/abs/2506.08199

Extracting Information About Publication Venues Using Citation-Informed Transformers
Scientific document embeddings contain a variety of rich features which can be harnessed for downstream tasks such as recommendation, ranking, and clustering. We explore which tangible insights can be drawn from scientific document embeddings to understand trends in computer science research featured across nine well-known venues. We collect approximately 60,000 scientific documents published between 2015 and 2023 and analyze their embeddings, which we produce with the SPECTER pre-trained langu…

This https://arxiv.org/abs/2412.02544 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Testing inflation on all scales: a case study with $α$-attractors
A plethora of inflationary models can produce interesting small-scale phenomenology, such as enhanced scalar fluctuations leading to primordial black hole (PBH) production and large scalar-induced GW. Nevertheless, good models must simultaneously explain current observations on all scales. In this work, we showcase our methodology to establish the small-scale phenomenology of inflationary models on firm grounds. We consider the case of hybrid $α$-attractors, and focus on a reduced parameter sp…

🇺🇦 #NowPlaying on #BBC6Music's #TheCraigCharlesFunkAndSoulShow
Fat Produce:
🎵 No Way
#FatProduce
https://fatproduce.bandcamp.com/album/no-way-54-46-was-my-number
https://open.spotify.com/track/655GfEtxXoADMMYxM0ZScy

This https://arxiv.org/abs/2409.09685 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On the critical finite-size gap scaling for frustration-free Hamiltonians
We prove that the critical finite-size gap scaling for frustration-free Hamiltonians is of inverse-square type. The result covers general graphs embedded in $\mathbb R^D$ and general finite-range interactions without requiring assumptions about the ground state correlations. Therefore, the inverse-square critical gap scaling is a robust, universal property of finite-range frustration-free Hamiltonians. This places further limits on their ability to produce conformal field theories in the contin…

"The Right Kind of Family is a cross-border reportage podcast series ... [which] ... uncovers the rise of the Political Network for Values, a global network of conservative and far-right organisations which is orchestrating a clampdown on sexual and reproductive health rights across Europe, in the name of the so-called natural family."
Available in English, French, German, Hungarian, Italian, Polish and Spanish.

The Right Kind of Family | WePod - We produce podcasts
The Right Kind of Family is a cross-border reportage podcast series in 6 episodes co-produced by El Paìs Audio, Chora Media, 444 and Europod.The series uncovers the rise of the Political Network for Values, a global network of conservative and far-right organisations which is orchestrating a clampdown on sexual and reproductive health rights across Europe, in the name of the so-called natural family.

Sources: Elon Musk engaged in intense drug use during the 2024 presidential campaign, as he juggled the messy consequences of efforts to produce more babies (New York Times)
https://www.nytimes.com/2025/05/30/us/elon

Elon Musk Juggled Drugs and Family Drama on Trump’s Campaign Trail
As Mr. Musk entered President Trump’s orbit, his private life grew increasingly tumultuous and his drug use was more intense than previously known.

I used to fantasize about video games wowing audiences by using AI to do things previously impossible.
Voiceovers using your chosen character name.
A “teleport in” effect using a latent space walk for a unique look.
Fighting game CPU opponents that feel human.
Pokémon games with all 1,025 mons and dozens of animations each.
But my fantasy will never come true. The features might appear, but anything AI will produce more controversy than wowing.
Justifiabl…

A construction that preserves the configuration of a matroid, with applications to lattice path matroids
Joseph E. Bonin, Anna de Mier
https://arxiv.org/abs/2506.06109

A construction that preserves the configuration of a matroid, with applications to lattice path matroids
The configuration of a matroid $M$ is the abstract lattice of cyclic flats (flats that are unions of circuits) where we record the size and rank of each cyclic flat, but not the set. One can compute the Tutte polynomial of $M$, and stronger invariants (notably, the $\mathcal{G}$-invariant), from the configuration. Given a matroid $M$ in which certain pairs of cyclic flats are non-modular, we show how to produce a matroid that is not isomorphic to $M$ but has the same configuration as $M$. We sh…

GNHeII J1236 6215: A He II $\lambda$1640 emitting and potentially LyC leaking galaxy at $z$ = 2.9803 unveiled through JWST & Keck observations
Chayan Mondal, Kanak Saha, Anshuman Borgohain, Brent M. Smith, Rogier A. Windhorst, Naveen Reddy, Chian-Chou Chen, Keiichi Umetsu, Rolf A. Jansen
https://arxiv.org/abs/2506.06831

GNHeII J1236+6215: A He II $λ$1640 emitting and potentially LyC leaking galaxy at $z$ = 2.9803 unveiled through JWST & Keck observations
He II $λ$1640 emission in galaxies indicates the presence of sources that produce extreme ionizing photons. Here, we report the discovery of a He II $λ$1640 emitting galaxy, GNHeII J1236+6215, at $z=$ 2.9803 in the GOODS-north field. We use photometry in 17 wavebands from near-UV to infrared to characterize the galaxy SED and combine Keck LRIS and JWST NIRSpec spectra to identify 15 emission lines including He II $λ$1640. We infer that the He$^+$ ionization in the galaxy could be driven by s…

This https://arxiv.org/abs/2207.03997 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Tutorial on Event Detection using Social Media Data Analysis: Applications, Challenges, and Open Problems
In recent years, social media has become one of the most popular platforms for communication. These platforms allow users to report real-world incidents that might swiftly and widely circulate throughout the whole social network. A social event is a real-world incident that is documented on social media. Social gatherings could contain vital documentation of crisis scenarios. Monitoring and analyzing this rich content can produce information that is extraordinarily valuable and help people and …

This https://arxiv.org/abs/2404.02791 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Thermodynamic limits on general far-from-equilibrium molecular templating networks
Cells produce RNA and proteins via molecular templating networks. We show that information transmission in such networks is bounded by functions of a simple thermodynamic property of the network, regardless of complexity. Surprisingly, putative systems operating at this bound do not have a high flux around the network. Instead, they have low entropy production, with each product in a ``pseudo-equilibrium'' determined by a single pathway. These pseudo-equilibrium limits constrain information tra…

RT @…
#Hackathon with a 💰 £4,000 prize pot will take place from 9am-3pm (CEST) on 11, 12 and 16 June.
Entrants will be expected to use new data collected via our web-first panel survey to produce policy-relevant insights.
Registration closes…

Hackathon: Analysing CRONOS data and communicating key insights to policy makers | Infra4NextGen
Save the date for our next Hackathon on reusing, analysing and visualizing Infra4NextGen data to win prizes in various categories!

This https://arxiv.org/abs/2504.12684 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGR_…

SOPHY: Learning to Generate Simulation-Ready Objects with Physical Materials
We present SOPHY, a generative model for 3D physics-aware shape synthesis. Unlike existing 3D generative models that focus solely on static geometry or 4D models that produce physics-agnostic animations, our method jointly synthesizes shape, texture, and material properties related to physics-grounded dynamics, making the generated objects ready for simulations and interactive, dynamic environments. To train our model, we introduce a dataset of 3D objects annotated with detailed physical materi…

New resonances at LHC
Alain Le Yaouanc, Fran\c{c}ois Richard
https://arxiv.org/abs/2506.09490 https://arxiv.org/pdf/2506.09490…

New resonances at LHC
Due to the large QCD background, the tt spectroscopy is poorly doing at LHC with the exception of a toponium type candidate observed with high statistical significance by CMS. Our previous work offers an alternate interpretation of this narrow resonance as a Kaluza Klein graviton. For heavy scalars, following ATLAS, we describe how the top loop contribution to the gluon-gluon fusion mechanisms could produce a dip rather than a bump in the mass distribution, which further complicates searches fo…

Longer Lists Yield Better Matchings
Yuri Faenza, Aapeli Vuorinen
https://arxiv.org/abs/2506.06217 https://arxiv.org/pdf/2506.06217

Longer Lists Yield Better Matchings
Many centralized mechanisms for two-sided matching markets that enjoy strong theoretical properties assume that the planner solicits full information on the preferences of each participating agent. In particular, they expect that participants compile and communicate their complete preference lists over agents from the other side of the market. However, real-world markets are often very large and agents cannot always be expected to even produce a ranking of all options on the other side. It is t…

Flow-Lenia: Emergent evolutionary dynamics in mass conservative continuous cellular automata
Erwan Plantec, Gautier Hamon, Mayalen Etcheverry, Bert Wang-Chak Chan, Pierre-Yves Oudeyer, Cl\'ement Moulin-Frier
https://arxiv.org/abs/2506.08569

Flow-Lenia: Emergent evolutionary dynamics in mass conservative continuous cellular automata
Central to the artificial life endeavour is the creation of artificial systems spontaneously generating properties found in the living world such as autopoiesis, self-replication, evolution and open-endedness. While numerous models and paradigms have been proposed, cellular automata (CA) have taken a very important place in the field notably as they enable the study of phenomenons like self-reproduction and autopoiesis. Continuous CA like Lenia have been showed to produce life-like patterns rem…

This https://arxiv.org/abs/2503.04791 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Development and Benchmarking of JANGOFETT: A Novel Geant4-Operated Fission Event Tracking Tool
Experiments measuring fission observables encounter false coincidences arising from timing overlap of separate fission product decays. Simulations of both fission observables and particles in detector systems exist, but have not yet been combined to produce accurate event-by-event outputs in a time-dependent manner. Geant4 is a powerful simulation tool for nuclear physics studies, but it does not handle multiple initial particles in a single simulation instance, nor does it feature high fidelit…

"The big problem is 'bottlenecks' that make it harder to produce housing, expand energy production, or build new roads and bridges."
vs.
"The big problem is that big corporations have way too much power over our economy and our government."
By 12pts all voters and by 42pts Dem voters prefer the second statement. They're right!

Poll: Democratic voters prefer "populism" over "abundance"
Democrats are asking themselves some hard questions as they ponder how they lost the 2024 election.

This https://arxiv.org/abs/2307.14634 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Fact-Checking of AI-Generated Reports
With advances in generative artificial intelligence (AI), it is now possible to produce realistic-looking automated reports for preliminary reads of radiology images. This can expedite clinical workflows, improve accuracy and reduce overall costs. However, it is also well-known that such models often hallucinate, leading to false findings in the generated reports. In this paper, we propose a new method of fact-checking of AI-generated reports using their associated images. Specifically, the dev…

A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms
Emma Harvey, Rene F. Kizilcec, Allison Koenecke
https://arxiv.org/abs/2506.04419

A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms
Increasingly, individuals who engage in online activities are expected to interact with large language model (LLM)-based chatbots. Prior work has shown that LLMs can display dialect bias, which occurs when they produce harmful responses when prompted with text written in minoritized dialects. However, whether and how this bias propagates to systems built on top of LLMs, such as chatbots, is still unclear. We conduct a review of existing approaches for auditing LLMs for dialect bias and show tha…

This https://arxiv.org/abs/2505.20302 has been replaced.
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VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification
This paper introduces VeriThoughts, a novel dataset designed for reasoning-based Verilog code generation. We establish a new benchmark framework grounded in formal verification methods to evaluate the quality and correctness of generated hardware descriptions. Additionally, we present a suite of specialized small-scale models optimized specifically for Verilog generation. Our work addresses the growing need for automated hardware design tools that can produce verifiably correct implementations …

from my link log —
A non-uniform quasirandom number generator for games.
https://taylorpetrick.com/blog/post/quasi-random-dist
saved 2024-08-15

A Quasi-Random Number Generator
I decided to implement a non-uniform random number generator for use in video games. The purpose of the technique is produce random events that are more consistent than a uniform distribution, similar to stratified sampling.

This https://arxiv.org/abs/2506.02943 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

A Multi-agent LLM-based JUit Test Generation with Strong Oracles
Unit testing plays a critical role in ensuring software correctness. However, writing unit tests manually is laborious, especially for strong typed languages like Java, motivating the need for automated approaches. Traditional methods primarily rely on search-based or randomized algorithms to generate tests that achieve high code coverage and produce regression oracles, which are derived from the program's current behavior rather than its intended functionality. Recent advances in large languag…

Computationally Intensive Research: Advancing a Role for Secondary Analysis of Qualitative Data
Kaveh Mohajeri, Amir Karami
https://arxiv.org/abs/2506.04230

Computationally Intensive Research: Advancing a Role for Secondary Analysis of Qualitative Data
This paper draws attention to the potential of computational methods in reworking data generated in past qualitative studies. While qualitative inquiries often produce rich data through rigorous and resource-intensive processes, much of this data usually remains unused. In this paper, we first make a general case for secondary analysis of qualitative data by discussing its benefits, distinctions, and epistemological aspects. We then argue for opportunities with computationally intensive seconda…

This https://arxiv.org/abs/2505.22772 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Calibrated Value-Aware Model Learning with Stochastic Environment Models
The idea of value-aware model learning, that models should produce accurate value estimates, has gained prominence in model-based reinforcement learning. The MuZero loss, which penalizes a model's value function prediction compared to the ground-truth value function, has been utilized in several prominent empirical works in the literature. However, theoretical investigation into its strengths and weaknesses is limited. In this paper, we analyze the family of value-aware model learning losses, w…

Learning to Recover: Dynamic Reward Shaping with Wheel-Leg Coordination for Fallen Robots
Boyuan Deng, Luca Rossini, Jin Wang, Weijie Wang, Nikolaos Tsagarakis
https://arxiv.org/abs/2506.05516

Learning to Recover: Dynamic Reward Shaping with Wheel-Leg Coordination for Fallen Robots
Adaptive recovery from fall incidents are essential skills for the practical deployment of wheeled-legged robots, which uniquely combine the agility of legs with the speed of wheels for rapid recovery. However, traditional methods relying on preplanned recovery motions, simplified dynamics or sparse rewards often fail to produce robust recovery policies. This paper presents a learning-based framework integrating Episode-based Dynamic Reward Shaping and curriculum learning, which dynamically bal…

This https://arxiv.org/abs/2410.12815 has been replaced.
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Expanding Over-the-Air Computation with Frequency Modulations
In this study we introduce Logarithmic Frequency Shift Keying (Log-FSK), a novel frequency modulation for over-the-air computation (AirComp). Log-FSK leverages non-linear signal processing to produce AirComp in the frequency domain, this is, the maximum frequency of the received signal corresponds to the sum of the individual transmitted frequencies. The demodulation procedure relies on the inverse Discrete Cosine Transform (DCT) and the extraction of the maximum frequency component. Log-FSK en…

Crappy weather or not, we will visit the farmers market this morning. I like supporting local farmers, and there is a major improvement in the quality and freshness of their produce versus the big chains. I also pay in cash, so they get EVERY dollar!
#shoplocal

A High-Performance Multilevel Framework for Quantum Layout Synthesis
Shuohao Ping, Naren Sathishkumar, Wan-Hsuan Lin, Hanyu Wang, Jason Cong
https://arxiv.org/abs/2505.24169

A High-Performance Multilevel Framework for Quantum Layout Synthesis
Quantum Layout Synthesis (QLS) is a critical compilation stage that adapts quantum circuits to hardware constraints with an objective of minimizing the SWAP overhead. While heuristic tools demonstrate good efficiency, they often produce suboptimal solutions, and exact methods suffer from limited scalability. In this work, we propose ML-SABRE, a high-performance multilevel framework for QLS that improves both solution quality and compilation time through a hierarchical optimization approach. We …

This https://arxiv.org/abs/2502.00278 has been replaced.
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BatAnalysis -- A Comprehensive Python Pipeline for Swift BAT Time-Tagged Event Data Analysis
The Swift Burst Alert Telescope (BAT) is a coded aperture gamma-ray instrument with a large field of view that was designed to detect and localize transient events. When a transient is detected, either on-board or externally, the BAT saves time-tagged event (TTE) data which provides the highest quality information of the locations of the photons on the detector plane and their energies. This data can be used to produce spectra, lightcurves, and sky images of a transient event. While these data …

Generalizations of Frobenius-Schur indicators from Kuperberg invariants
Liang Chang, Siu-Hung Ng, Yilong Wang
https://arxiv.org/abs/2506.07409 https://

Generalizations of Frobenius-Schur indicators from Kuperberg invariants
We introduce an approach to produce gauge invariants of any finite-dimensional Hopf algebras from the Kuperberg invariants of framed 3-manifolds. These invariants are generalizations of Frobenius-Schur indicators of Hopf algebras. The computation of Kuperberg invariants is based on a presentation of the framed 3-manifold in terms of Heegaard diagram with combings satisfying certain admissibility conditions. We provide framed Heegaard diagrams for two infinite families of small genus 3-manifolds…

I find the deluge of information overwhelming and things have only gotten worse with AI. Now I can produce mountains of crap using AI and then I have to sift it to see if there is anything worth saving.
I find myself always behind on working through all the information and projects I have...and if by some Herculean effort I manage to get current (this usually involves hitting the delete button repeatedly while telling myself "you'll never use that or need that again") I find myself building a mountain again with great haste!
Yes, I am fully aware I'm #neurodivergent and #adhd. Sigh.

I'm baffled that this guy is a respected analyst. Yeah, an infinite number of AI agents will spend their money on content from human creators, making those humans infinitely rich. I see no flaws in this model.

Quantum cosmological perturbations in bouncing models with mimetic dark matter
Idaiane L. Machado, D\^eivid R. da Silva, Nelson Pinto-Neto
https://arxiv.org/abs/2506.06901

Quantum cosmological perturbations in bouncing models with mimetic dark matter
We calculate the power spectrum of cosmological perturbations originated from quantum vacuum fluctuations in bouncing scenarios proposed in Ref.~\cite{chamseddine2014cosmology} in the framework of mimetic cosmology. We show that all physically relevant models produce scale invariant spectral indices, and amplitudes compatible with observations provided that the bounce occurs at length scales $t_0$ inside the physically reasonable interval $10^5 l_p < t_0 < 10^9 l_p$. We also show that by slight…

What the last 5 years of the NFL Draft tells us about college football recruiting https://www.nytimes.com/athletic/6402371/2025/06/05/nfl-draft-college-football-recruiting-2/

Private GPTs for LLM-driven testing in software development and machine learning
Jakub Jagielski, Markus Abel
https://arxiv.org/abs/2506.06509 https://

Private GPTs for LLM-driven testing in software development and machine learning
In this contribution, we examine the capability of private GPTs to automatically generate executable test code based on requirements. More specifically, we use acceptance criteria as input, formulated as part of epics, or stories, which are typically used in modern development processes. This gives product owners, or business intelligence, respectively, a way to directly produce testable criteria through the use of LLMs. We explore the quality of the so-produced tests in two ways: i) directly b…

An Execution Model for RICE
Steven Libby
https://arxiv.org/abs/2506.05839 https://arxiv.org/pdf/2506.05839

An Execution Model for RICE
In this paper, we build on the previous work of the RICE compiler by giving its execution model. We show the restrictions to the FlatCurry language that were made to produce executable code, and present the execution model using operational semantics similar to Launchbury. Finally, we show that the execution model conforms with the standard operational semantics for Curry.

This https://arxiv.org/abs/2505.24718 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Reinforcing Video Reasoning with Focused Thinking
Recent advancements in reinforcement learning, particularly through Group Relative Policy Optimization (GRPO), have significantly improved multimodal large language models for complex reasoning tasks. However, two critical limitations persist: 1) they often produce unfocused, verbose reasoning chains that obscure salient spatiotemporal cues and 2) binary rewarding fails to account for partially correct answers, resulting in high reward variance and inefficient learning. In this paper, we propos…

This https://arxiv.org/abs/2502.18504 has been replaced.
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TurboFuzzLLM: Turbocharging Mutation-based Fuzzing for Effectively Jailbreaking Large Language Models in Practice
Jailbreaking large-language models (LLMs) involves testing their robustness against adversarial prompts and evaluating their ability to withstand prompt attacks that could elicit unauthorized or malicious responses. In this paper, we present TurboFuzzLLM, a mutation-based fuzzing technique for efficiently finding a collection of effective jailbreaking templates that, when combined with harmful questions, can lead a target LLM to produce harmful responses through black-box access via user prompt…

This https://arxiv.org/abs/2408.01583 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Superconducting Levitated Detector of Gravitational Waves
A magnetically levitated mass couples to gravity and can act as an effective gravitational wave detector. We show that a superconducting sphere levitated in a quadrupolar magnetic field, when excited by a gravitational wave, will produce magnetic field fluctuations that can be read out using a flux tunable microwave resonator. With a readout operating at the standard quantum limit, such a system could achieve broadband strain noise sensitivity of $h \lesssim 10^{-20}/\sqrt{\rm Hz}$ for frequenc…

🔫 From Civil Wars to Neoliberalism in Central America
#globalsouth

From Civil Wars to Neoliberalism in Central America
The end of the bloody, US-backed civil wars across Central America led to a brutal neoliberal economic restructuring near the turn of the century — which then helped produce the 21st-century authoritarianism of Salvadoran president Nayib Bukele.

This https://arxiv.org/abs/2502.12089 has been replaced.
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How Compositional Generalization and Creativity Improve as Diffusion Models are Trained
Natural data is often organized as a hierarchical composition of features. How many samples do generative models need in order to learn the composition rules, so as to produce a combinatorially large number of novel data? What signal in the data is exploited to learn those rules? We investigate these questions in the context of diffusion models both theoretically and empirically. Theoretically, we consider a simple probabilistic context-free grammar - a tree-like graphical model used to represe…

BASIL: Best-Action Symbolic Interpretable Learning for Evolving Compact RL Policies
Kourosh Shahnazari, Seyed Moein Ayyoubzadeh, Mohammadali Keshtparvar
https://arxiv.org/abs/2506.00328

BASIL: Best-Action Symbolic Interpretable Learning for Evolving Compact RL Policies
The quest for interpretable reinforcement learning is a grand challenge for the deployment of autonomous decision-making systems in safety-critical applications. Modern deep reinforcement learning approaches, while powerful, tend to produce opaque policies that compromise verification, reduce transparency, and impede human oversight. To address this, we introduce BASIL (Best-Action Symbolic Interpretable Learning), a systematic approach for generating symbolic, rule-based policies via online ev…

TRUST: Test-time Resource Utilization for Superior Trustworthiness
Haripriya Harikumar, Santu Rana
https://arxiv.org/abs/2506.06048 https://

TRUST: Test-time Resource Utilization for Superior Trustworthiness
Standard uncertainty estimation techniques, such as dropout, often struggle to clearly distinguish reliable predictions from unreliable ones. We attribute this limitation to noisy classifier weights, which, while not impairing overall class-level predictions, render finer-level statistics less informative. To address this, we propose a novel test-time optimization method that accounts for the impact of such noise to produce more reliable confidence estimates. This score defines a monotonic subs…

Nonminimal infrared gravitational reheating in light of ACT
Ayan Chakraborty, Debaprasad Maity, Rajesh Mondal
https://arxiv.org/abs/2506.02141 https://

Nonminimal infrared gravitational reheating in light of ACT
Inflation is known to produce large infrared scalar fluctuations. Further, if a scalar field $(χ)$ is non-minimally coupled with gravity through $ξχ^2 R$, those infrared modes experience \textit{tachyonic instability} during and after inflation. Those large non-perturbative infrared modes can collectively produce hot Big Bang universe upon their horizon entry during the post-inflationary period. We indeed find that for reheating equation of state (EoS), $w_ϕ > 1/3$, and coupling strength, $…

Flare frequency in M dwarfs belonging to Young Moving Groups
E. Mamonova, Y. Shan, A. F. Kowalski, S. Wedemeyer S. C. Werner
https://arxiv.org/abs/2506.04465

Flare frequency in M dwarfs belonging to Young Moving Groups
Context. M stars are preferred targets for studying terrestrial exoplanets, for which we hope to obtain their atmosphere spectra in the next decade. However, M dwarfs have long been known for strong magnetic activity and the ability to frequently produce optical, broadband emission flares. Aims. We aim to characterise the flaring behaviour of young M dwarfs in the temporal, spectral, and energetic dimensions, as well as examine the stellar parameters governing this behaviour, in order to improv…

Machine vs Machine: Using AI to Tackle Generative AI Threats in Assessment
Mohammad Saleh Torkestani, Taha Mansouri
https://arxiv.org/abs/2506.02046 https:…

Machine vs Machine: Using AI to Tackle Generative AI Threats in Assessment
This paper presents a theoretical framework for addressing the challenges posed by generative artificial intelligence (AI) in higher education assessment through a machine-versus-machine approach. Large language models like GPT-4, Claude, and Llama increasingly demonstrate the ability to produce sophisticated academic content, traditional assessment methods face an existential threat, with surveys indicating 74-92% of students experimenting with these tools for academic purposes. Current respon…

This https://arxiv.org/abs/2503.14031 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Debiased Opto-electronic Joint Transform Correlator for Enhanced Real-Time Pattern Recognition
Opto-electronic joint transform correlators (OJTCs) use a focal plane array (FPA) to detect the joint power spectrum (JPS) of two input images, projecting it onto a spatial light modulator (SLM) to be optically Fourier transformed. The JPS is composed of two self-intensities and two conjugate-products, where only the latter produce the cross-correlation. However, the self-intensity terms are typically much stronger than the conjugate-products, producing a bias that consumes most of the availabl…

This https://arxiv.org/abs/2410.17968 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Novel approach to investigate ATOMKI anomaly using Coherent CAPTAIN-Mills detectors
ATOMKI nuclear anomaly has suggested a new BSM (Beyond the Standard Model) boson with mass $\sim17$ MeV emitted from excited nuclei and quickly decays into a pair of $e^+e^-$. In order to search for the new particle, we propose a new approach that utilizes the ongoing Coherent CAPTAIN-Mills (CCM) 10-ton LAr (liquid argon) detectors. The neutrons from the Lujan target can scatter inelastically by the PMT glass in the CCM detector can produce the new boson which solves the ATOMKI anomaly. The new…

Browns DC Jim Schwartz expects career year from Myles Garrett following record-setting contract https://www.nfl.com/news/browns-dc-jim-schwartz-expects-career-year-from-myles-garrett-following-record-setting-contra…

This https://arxiv.org/abs/2505.20573 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Collision- and Reachability-Aware Multi-Robot Control with Grounded LLM Planners
Large language models (LLMs) have demonstrated strong performance in various robot control tasks. However, their deployment in real-world applications remains constrained. Even state-ofthe-art LLMs, such as GPT-o4mini, frequently produce invalid action plans that violate physical constraints, such as directing a robot to an unreachable location or causing collisions between robots. This issue primarily arises from a lack of awareness of these physical constraints during the reasoning process. T…

A tertiary review on quantum cryptography
Luiz Filipi Anderson de Sousa Moura, Carlos Becker Westphall
https://arxiv.org/abs/2506.02028 https://

A tertiary review on quantum cryptography
Quantum computers impose an immense threat to system security. As a countermeasure, new cryptographic classes have been created to prevent these attacks. Technologies such as post-quantum cryptography and quantum cryptography. Quantum cryptography uses the principle of quantum physics to produce theoretically unbreakable security. This tertiary review selected 51 secondary studies from the Scopus database and presented bibliometric analysis, a list of the main techniques used in the field, and …

Evaluating the Contextual Integrity of False Positives in Algorithmic Travel Surveillance
Alina Wernick, Alan Medlar, Sofia S\"oderholm, Dorota G{\l}owacka
https://arxiv.org/abs/2506.00218

Evaluating the Contextual Integrity of False Positives in Algorithmic Travel Surveillance
International air travel is highly surveilled. While surveillance is deemed necessary for law enforcement to prevent and detect terrorism and other serious crimes, even the most accurate algorithmic mass surveillance systems produce high numbers of false positives. Despite the potential impact of false positives on the fundamental rights of millions of passengers, algorithmic travel surveillance is lawful in the EU. However, as the system's processing practices and accuracy are kept secret by l…

This https://arxiv.org/abs/2506.02943 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

A Multi-agent LLM-based JUit Test Generation with Strong Oracles
Unit testing plays a critical role in ensuring software correctness. However, writing unit tests manually is laborious, especially for strong typed languages like Java, motivating the need for automated approaches. Traditional methods primarily rely on search-based or randomized algorithms to generate tests that achieve high code coverage and produce regression oracles, which are derived from the program's current behavior rather than its intended functionality. Recent advances in large languag…

Geometric Visual Servo Via Optimal Transport
Ethan Canzini, Simon Pope, Ashutosh Tiwari
https://arxiv.org/abs/2506.02768 https://arxi…

Geometric Visual Servo Via Optimal Transport
When developing control laws for robotic systems, the principle factor when examining their performance is choosing inputs that allow smooth tracking to a reference input. In the context of robotic manipulation, this involves translating an object or end-effector from an initial pose to a target pose. Robotic manipulation control laws frequently use vision systems as an error generator to track features and produce control inputs. However, current control algorithms don't take into account the …

A Multi-agent LLM-based JUit Test Generation with Strong Oracles
Qinghua Xu, Guancheng Wang, Lionel Briand, Kui Liu
https://arxiv.org/abs/2506.02943 https:…

A Multi-agent LLM-based JUit Test Generation with Strong Oracles
Unit testing plays a critical role in ensuring software correctness. However, writing unit tests manually is laborious, especially for strong typed languages like Java, motivating the need for automated approaches. Traditional methods primarily rely on search-based or randomized algorithms to generate tests that achieve high code coverage and produce regression oracles, which are derived from the program's current behavior rather than its intended functionality. Recent advances in large languag…

This https://arxiv.org/abs/2504.21841 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Neuro-Symbolic Generation of Explanations for Robot Policies with Weighted Signal Temporal Logic
Neural network-based policies have demonstrated success in many robotic applications, but often lack human-explanability, which poses challenges in safety-critical deployments. To address this, we propose a neuro-symbolic explanation framework that generates a weighted signal temporal logic (wSTL) specification to describe a robot policy in a interpretable form. Existing methods typically produce explanations that are verbose and inconsistent, which hinders explainability, and loose, which do n…

This https://arxiv.org/abs/2404.19318 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Calibration of Large Language Models on Code Summarization
A brief, fluent, and relevant summary can be helpful during program comprehension; however, such a summary does require significant human effort to produce. Often, good summaries are unavailable in software projects, which makes maintenance more difficult. There has been a considerable body of research into automated AI-based methods, using Large Language models (LLMs), to generate summaries of code; there also has been quite a bit of work on ways to measure the performance of such summarizatio…

This https://arxiv.org/abs/2502.11475 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Focused-DPO: Enhancing Code Generation Through Focused Preference Optimization on Error-Prone Points
Code generation models have shown significant potential for automating programming tasks. However, the challenge of generating accurate and reliable code persists due to the highly complex and long-reasoning nature of the task. Even state-of-the-art models often fail in code generation due to small errors, which can drastically affect the overall functionality of code. Our study identifies that current models tend to produce errors concentrated at specific error-prone points, which significantl…

This https://arxiv.org/abs/2411.03079 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Utilizing Precise and Complete Code Context to Guide LLM in Automatic False Positive Mitigation
Static Application Security Testing (SAST) tools are critical to software quality, identifying potential code issues early in development. However, they often produce false positive warnings that require manual review, slowing down development. Thus, automating false positive mitigation (FPM) is essential. The advent of Large Language Models (LLMs), with their strong abilities in natural language and code understanding, offers promising avenues for FPM. Yet current LLM-based FPM method faces tw…