Tootfinder

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[2/5]:
- POTSA: A Cross-Lingual Speech Alignment Framework for Speech-to-Text Translation
Li, Cui, Wang, Ge, Huang, Li, Peng, Lu, Tashi, Wang, Dang
https://arxiv.org/abs/2511.09232 https://mastoxiv.page/@arXiv_csCL_bot/115541846907664054
- Beyond Elicitation: Provision-based Prompt Optimization for Knowledge-Intensive Tasks
Yunzhe Xu, Zhuosheng Zhang, Zhe Liu
https://arxiv.org/abs/2511.10465 https://mastoxiv.page/@arXiv_csCL_bot/115547607561282911
- $\pi$-Attention: Periodic Sparse Transformers for Efficient Long-Context Modeling
Dong Liu, Yanxuan Yu
https://arxiv.org/abs/2511.10696 https://mastoxiv.page/@arXiv_csCL_bot/115564418836654965
- Based on Data Balancing and Model Improvement for Multi-Label Sentiment Classification Performanc...
Zijin Su, Huanzhu Lyu, Yuren Niu, Yiming Liu
https://arxiv.org/abs/2511.14073 https://mastoxiv.page/@arXiv_csCL_bot/115575715073023141
- HEAD-QA v2: Expanding a Healthcare Benchmark for Reasoning
Alexis Correa-Guill\'en, Carlos G\'omez-Rodr\'iguez, David Vilares
https://arxiv.org/abs/2511.15355 https://mastoxiv.page/@arXiv_csCL_bot/115581410328165116
- Towards Hyper-Efficient RAG Systems in VecDBs: Distributed Parallel Multi-Resolution Vector Search
Dong Liu, Yanxuan Yu
https://arxiv.org/abs/2511.16681 https://mastoxiv.page/@arXiv_csCL_bot/115603508442305146
- Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Transla...
Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, Marika Borovikova, Dage S\"arg, Kairit Sirts
https://arxiv.org/abs/2511.17290 https://mastoxiv.page/@arXiv_csCL_bot/115604083224487885
- A Systematic Study of In-the-Wild Model Merging for Large Language Models
O\u{g}uz Ka\u{g}an Hitit, Leander Girrbach, Zeynep Akata
https://arxiv.org/abs/2511.21437 https://mastoxiv.page/@arXiv_csCL_bot/115621178703846052
- CREST: Universal Safety Guardrails Through Cluster-Guided Cross-Lingual Transfer
Lavish Bansal, Naman Mishra
https://arxiv.org/abs/2512.02711 https://mastoxiv.page/@arXiv_csCL_bot/115655090475535157
- Multilingual Medical Reasoning for Question Answering with Large Language Models
Pietro Ferrazzi, Aitor Soroa, Rodrigo Agerri
https://arxiv.org/abs/2512.05658 https://mastoxiv.page/@arXiv_csCL_bot/115683267711014189
- OnCoCo 1.0: A Public Dataset for Fine-Grained Message Classification in Online Counseling Convers...
Albrecht, Lehmann, Poltermann, Rudolph, Steigerwald, Stieler
https://arxiv.org/abs/2512.09804 https://mastoxiv.page/@arXiv_csCL_bot/115700409397020978
- Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, an...
Hanyu Cai, Binqi Shen, Lier Jin, Lan Hu, Xiaojing Fan
https://arxiv.org/abs/2512.12812 https://mastoxiv.page/@arXiv_csCL_bot/115729149622659403
- Beg to Differ: Understanding Reasoning-Answer Misalignment Across Languages
Ovalle, Ross, Ruder, Williams, Ullrich, Ibrahim, Sagun
https://arxiv.org/abs/2512.22712 https://mastoxiv.page/@arXiv_csCL_bot/115808161882146194
- Activation Steering for Masked Diffusion Language Models
Adi Shnaidman, Erin Feiglin, Osher Yaari, Efrat Mentel, Amit Levi, Raz Lapid
https://arxiv.org/abs/2512.24143 https://mastoxiv.page/@arXiv_csCL_bot/115819533211103315
- JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese L...
Liu, Li, Niu, Zhang, Xun, Hou, Wang, Iwasawa, Matsuo, Hatakeyama-Sato
https://arxiv.org/abs/2601.01627 https://mastoxiv.page/@arXiv_csCL_bot/115847901607405421
- FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAG
Dassen, Kotula, Murray, Yates, Lawrie, Kayi, Mayfield, Duh
https://arxiv.org/abs/2601.05866 https://mastoxiv.page/@arXiv_csCL_bot/115881545684182376
- {\dag}DAGGER: Distractor-Aware Graph Generation for Executable Reasoning in Math Problems
Zabir Al Nazi, Shubhashis Roy Dipta, Sudipta Kar
https://arxiv.org/abs/2601.06853 https://mastoxiv.page/@arXiv_csCL_bot/115887753245730019
- Symphonym: Universal Phonetic Embeddings for Cross-Script Name Matching
Stephen Gadd
https://arxiv.org/abs/2601.06932 https://mastoxiv.page/@arXiv_csCL_bot/115887767008671765
- LLMs versus the Halting Problem: Revisiting Program Termination Prediction
Sultan, Armengol-Estape, Kesseli, Vanegue, Shahaf, Adi, O'Hearn
https://arxiv.org/abs/2601.18987 https://mastoxiv.page/@arXiv_csCL_bot/115972010510378715
- MuVaC: A Variational Causal Framework for Multimodal Sarcasm Understanding in Dialogues
Diandian Guo, Fangfang Yuan, Cong Cao, Xixun Lin, Chuan Zhou, Hao Peng, Yanan Cao, Yanbing Liu
https://arxiv.org/abs/2601.20451 https://mastoxiv.page/@arXiv_csCL_bot/115977891530875024
toXiv_bot_toot

wir schreiben das jahr 2026 – und immer noch gibt es journals mit page und colour charges. 🙄
dieses beispiel: https://ar.iiarjournals.org/content/instructions-authors

OK, Beowulf bug. Both EVAL and APPLY in Beowulf are straight transcriptions of the mexprs on pages 70 and 71 of the #Lisp 1.5 Porgammer's Manual.
CONC is the only FEXPR I have implemented so far (and one of only three FEXPRs in the manual).
The unit test for CONC fails, because EVLIS is called on the argument list by EVAL (line 20 on page 71) before it reaches APPLY, and therefore b…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[1/5]:
- Beyond In-Distribution Success: Scaling Curves of CoT Granularity for Language Model Generalization
Ru Wang, Wei Huang, Selena Song, Haoyu Zhang, Qian Niu, Yusuke Iwasawa, Yutaka Matsuo, Jiaxian Guo
https://arxiv.org/abs/2502.18273 https://mastoxiv.page/@arXiv_csCL_bot/114069031700102129
- Benchmarking NLP-supported Language Sample Analysis for Swiss Children's Speech
Anja Ryser, Yingqiang Gao, Sarah Ebling
https://arxiv.org/abs/2504.00780 https://mastoxiv.page/@arXiv_csCL_bot/114267149909002069
- Cultural Biases of Large Language Models and Humans in Historical Interpretation
Fabio Celli, Georgios Spathulas
https://arxiv.org/abs/2504.02572 https://mastoxiv.page/@arXiv_csCL_bot/114278467094094490
- BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text
Jiageng Wu, et al.
https://arxiv.org/abs/2504.19467 https://mastoxiv.page/@arXiv_csCL_bot/114420036189999973
- Understanding the Anchoring Effect of LLM with Synthetic Data: Existence, Mechanism, and Potentia...
Yiming Huang, Biquan Bie, Zuqiu Na, Weilin Ruan, Songxin Lei, Yutao Yue, Xinlei He
https://arxiv.org/abs/2505.15392 https://mastoxiv.page/@arXiv_csCL_bot/114550277171100272
- Just as Humans Need Vaccines, So Do Models: Model Immunization to Combat Falsehoods
Raza, Qureshi, Farooq, Lotif, Chadha, Pandya, Emmanouilidis
https://arxiv.org/abs/2505.17870 https://mastoxiv.page/@arXiv_csCL_bot/114572956853819813
- LingoLoop Attack: Trapping MLLMs via Linguistic Context and State Entrapment into Endless Loops
Fu, Jiang, Hong, Li, Guo, Yang, Chen, Zhang
https://arxiv.org/abs/2506.14493 https://mastoxiv.page/@arXiv_csCL_bot/114703502552989170
- GHTM: A Graph-based Hybrid Topic Modeling Approach with a Benchmark Dataset for the Low-Resource ...
Farhana Haque, Md. Abdur Rahman, Sumon Ahmed
https://arxiv.org/abs/2508.00605 https://mastoxiv.page/@arXiv_csCL_bot/114969875643478303
- Link Prediction for Event Logs in the Process Industry
Anastasia Zhukova, Thomas Walton, Christian E. Lobm\"uller, Bela Gipp
https://arxiv.org/abs/2508.09096 https://mastoxiv.page/@arXiv_csCL_bot/115020938764936882
- AirQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation
Huang, Cao, Zhang, Kang, Wang, Wang, Luo, Zheng, Qian, Chen, Yu
https://arxiv.org/abs/2509.16952 https://mastoxiv.page/@arXiv_csCL_bot/115253526588472475
- Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortio...
Jun Seo Kim, Hyemi Kim, Woo Joo Oh, Hongjin Cho, Hochul Lee, Hye Hyeon Kim
https://arxiv.org/abs/2509.17292 https://mastoxiv.page/@arXiv_csCL_bot/115253586227941157
- Dual-Space Smoothness for Robust and Balanced LLM Unlearning
Han Yan, Zheyuan Liu, Meng Jiang
https://arxiv.org/abs/2509.23362 https://mastoxiv.page/@arXiv_csCL_bot/115293308293558024
- The Rise of AfricaNLP: Contributions, Contributors, Community Impact, and Bibliometric Analysis
Tadesse Destaw Belay, et al.
https://arxiv.org/abs/2509.25477 https://mastoxiv.page/@arXiv_csCL_bot/115298213432594791
- Open ASR Leaderboard: Towards Reproducible and Transparent Multilingual and Long-Form Speech Reco...
Srivastav, Zheng, Bezzam, Le Bihan, Koluguri, \.Zelasko, Majumdar, Moumen, Gandhi
https://arxiv.org/abs/2510.06961 https://mastoxiv.page/@arXiv_csCL_bot/115343748052193267
- Neuron-Level Analysis of Cultural Understanding in Large Language Models
Taisei Yamamoto, Ryoma Kumon, Danushka Bollegala, Hitomi Yanaka
https://arxiv.org/abs/2510.08284 https://mastoxiv.page/@arXiv_csCL_bot/115349533441895984
- CLMN: Concept based Language Models via Neural Symbolic Reasoning
Yibo Yang
https://arxiv.org/abs/2510.10063 https://mastoxiv.page/@arXiv_csCL_bot/115372392366793754
- Schema for In-Context Learning
Chen, Chen, Wang, Leong, Fung, Bernales, Aspuru-Guzik
https://arxiv.org/abs/2510.13905 https://mastoxiv.page/@arXiv_csCL_bot/115389057899856601
- Evaluating Latent Knowledge of Public Tabular Datasets in Large Language Models
Matteo Silvestri, Fabiano Veglianti, Flavio Giorgi, Fabrizio Silvestri, Gabriele Tolomei
https://arxiv.org/abs/2510.20351 https://mastoxiv.page/@arXiv_csCL_bot/115428615784704418
- LuxIT: A Luxembourgish Instruction Tuning Dataset from Monolingual Seed Data
Julian Valline, Cedric Lothritz, Siwen Guo, Jordi Cabot
https://arxiv.org/abs/2510.24434 https://mastoxiv.page/@arXiv_csCL_bot/115457025096322944
- Surfacing Subtle Stereotypes: A Multilingual, Debate-Oriented Evaluation of Modern LLMs
Muhammed Saeed, Muhammad Abdul-mageed, Shady Shehata
https://arxiv.org/abs/2511.01187 https://mastoxiv.page/@arXiv_csCL_bot/115491321130591723
toXiv_bot_toot

I’m not going to say that I "love" LibreOffice but I have used it for over a decade because a few times a month I need to do spreadsheety things, so almost every time it adds a menu to the menu bar (with a little globe for some reason) that takes me to this dialog.
In my years using LO, the only changes have been the version numbers. Given how "Download…" has always gone to a donation page, I feel certain that there’s no intention of automatic download *ever* being…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[4/5]:
- Retrieving Climate Change Disinformation by Narrative
Upravitelev, Solopova, Jakob, Sahitaj, M\"oller, Schmitt
https://arxiv.org/abs/2603.22015 https://mastoxiv.page/@arXiv_csCL_bot/116283633674519408
- PaperVoyager : Building Interactive Web with Visual Language Models
Dasen Dai, Biao Wu, Meng Fang, Wenhao Wang
https://arxiv.org/abs/2603.22999 https://mastoxiv.page/@arXiv_csCL_bot/116289015432093128
- Continual Robot Skill and Task Learning via Dialogue
Weiwei Gu, Suresh Kondepudi, Anmol Gupta, Lixiao Huang, Nakul Gopalan
https://arxiv.org/abs/2409.03166 https://mastoxiv.page/@arXiv_csRO_bot/113089412115632702
- Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs
Zara Siddique, Irtaza Khalid, Liam D. Turner, Luis Espinosa-Anke
https://arxiv.org/abs/2503.05371 https://mastoxiv.page/@arXiv_csLG_bot/114136994263573386
- SkillFlow: Scalable and Efficient Agent Skill Retrieval System
Fangzhou Li, Pagkratios Tagkopoulos, Ilias Tagkopoulos
https://arxiv.org/abs/2504.06188 https://mastoxiv.page/@arXiv_csAI_bot/114306773220502860
- Large Language Models for Computer-Aided Design: A Survey
Licheng Zhang, Bach Le, Naveed Akhtar, Siew-Kei Lam, Tuan Ngo
https://arxiv.org/abs/2505.08137 https://mastoxiv.page/@arXiv_csLG_bot/114504972217393639
- Structured Agent Distillation for Large Language Model
Liu, Kong, Dong, Yang, Li, Tang, Yuan, Niu, Zhang, Zhao, Lin, Huang, Wang
https://arxiv.org/abs/2505.13820 https://mastoxiv.page/@arXiv_csLG_bot/114544636506163783
- VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction
Fan, Zhang, Li, Zhang, Chen, Hu, Wang, Qu, Zhou, Wang, Yan, Xu, Theiss, Chen, Li, Tu, Wang, Ranjan
https://arxiv.org/abs/2505.20279 https://mastoxiv.page/@arXiv_csCV_bot/114578817567171199
- Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification
Bhattacharjee, Tian, Rubin, Lo, Merchant, Hanson, Gounley, Tandon
https://arxiv.org/abs/2506.04450 https://mastoxiv.page/@arXiv_csCR_bot/114635189706505648
- L-MARS: Legal Multi-Agent Workflow with Orchestrated Reasoning and Agentic Search
Ziqi Wang, Boqin Yuan
https://arxiv.org/abs/2509.00761 https://mastoxiv.page/@arXiv_csAI_bot/115140304787881576
- Your Models Have Thought Enough: Training Large Reasoning Models to Stop Overthinking
Han, Huang, Liao, Jiang, Lu, Zhao, Wang, Zhou, Jiang, Liang, Zhou, Sun, Yu, Xiao
https://arxiv.org/abs/2509.23392 https://mastoxiv.page/@arXiv_csAI_bot/115293169353788311
- Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models
Leander Girrbach, Stephan Alaniz, Genevieve Smith, Trevor Darrell, Zeynep Akata
https://arxiv.org/abs/2510.03721 https://mastoxiv.page/@arXiv_csCV_bot/115332690912652473
- Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Zhang, Hu, Upasani, Ma, Hong, Kamanuru, Rainton, Wu, Ji, Li, Thakker, Zou, Olukotun
https://arxiv.org/abs/2510.04618 https://mastoxiv.page/@arXiv_csLG_bot/115332999596603375
- Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling
Giannone, Xu, Nayak, Awhad, Sudalairaj, Xu, Srivastava
https://arxiv.org/abs/2510.05825 https://mastoxiv.page/@arXiv_csLG_bot/115338159696513898
- Complete asymptotic type-token relationship for growing complex systems with inverse power-law co...
Pablo Rosillo-Rodes, Laurent H\'ebert-Dufresne, Peter Sheridan Dodds
https://arxiv.org/abs/2511.02069 https://mastoxiv.page/@arXiv_physicssocph_bot/115496283627867809
- ViPRA: Video Prediction for Robot Actions
Sandeep Routray, Hengkai Pan, Unnat Jain, Shikhar Bahl, Deepak Pathak
https://arxiv.org/abs/2511.07732 https://mastoxiv.page/@arXiv_csRO_bot/115535941444003568
- AISAC: An Integrated multi-agent System for Transparent, Retrieval-Grounded Scientific Assistance
Chandrachur Bhattacharya, Sibendu Som
https://arxiv.org/abs/2511.14043
- VideoARM: Agentic Reasoning over Hierarchical Memory for Long-Form Video Understanding
Yufei Yin, Qianke Meng, Minghao Chen, Jiajun Ding, Zhenwei Shao, Zhou Yu
https://arxiv.org/abs/2512.12360 https://mastoxiv.page/@arXiv_csCV_bot/115729238732682644
- RadImageNet-VQA: A Large-Scale CT and MRI Dataset for Radiologic Visual Question Answering
L\'eo Butsanets, Charles Corbi\`ere, Julien Khlaut, Pierre Manceron, Corentin Dancette
https://arxiv.org/abs/2512.17396 https://mastoxiv.page/@arXiv_csCV_bot/115762705911757243
- Measuring all the noises of LLM Evals
Sida Wang
https://arxiv.org/abs/2512.21326 https://mastoxiv.page/@arXiv_csLG_bot/115779597137785637
toXiv_bot_toot

This was basically my day today.
- Get the wee one fed and dressed.
- While husband drives the wee one to 3yo preschool, I catch a bus to go to 10am movie screening with friend.
- During the movie, my phone was on silent but... received a call from CYF, a text from CYF, texts from the wee one's mother, email from CYF, email from preschool re Covid exposure (movie was approx 2.5 hours).
- Come straight home to do some work.
- Fill out 10 page carer assessment f…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[5/5]:
- AppellateGen: A Benchmark for Appellate Legal Judgment Generation
Yang, Wang, Fan, Hu, Wang, Liu, Zeng, Fu, Gong, Zhang, Li, Zheng, Xu
https://arxiv.org/abs/2601.01331 https://mastoxiv.page/@arXiv_csCY_bot/115847038572575387
- Vision-Language Agents for Interactive Forest Change Analysis
James Brock, Ce Zhang, Nantheera Anantrasirichai
https://arxiv.org/abs/2601.04497 https://mastoxiv.page/@arXiv_csCV_bot/115864542639529766
- FigEx2: Visual-Conditioned Panel Detection and Captioning for Scientific Compound Figures
Jifeng Song, Arun Das, Pan Wang, Hui Ji, Kun Zhao, Yufei Huang
https://arxiv.org/abs/2601.08026 https://mastoxiv.page/@arXiv_csCV_bot/115892719657942341
- Sparse-RL: Breaking the Memory Wall in LLM Reinforcement Learning via Stable Sparse Rollouts
Luo, Zhang, Hu, Zhang, Wang, Su, Sun, Liang, Zhang
https://arxiv.org/abs/2601.10079 https://mastoxiv.page/@arXiv_csLG_bot/115904206341755873
- Compounding Disadvantage: Auditing Intersectional Bias in LLM-Generated Explanations Across India...
Amogh Gupta (Neil), Niharika Patil (Neil), Sourojit Ghosh (Neil), SnehalKumar (Neil), S Gaikwad
https://arxiv.org/abs/2601.14506 https://mastoxiv.page/@arXiv_csCY_bot/115937624654783353
- Measuring Complexity at the Requirements Stage: Spectral Metrics as Development Effort Predictors
Vierlboeck, Pugliese, Nilchian, Grogan, Babu
https://arxiv.org/abs/2602.07182 https://mastoxiv.page/@arXiv_csSE_bot/116045826365214235
- CoPE-VideoLM: Leveraging Codec Primitives For Efficient Video Language Modeling
Sarkar, Pautrat, Miksik, Pollefeys, Armeni, Rad, Dusmanu
https://arxiv.org/abs/2602.13191 https://mastoxiv.page/@arXiv_csCV_bot/116079824094529198
- MoD-DPO: Towards Mitigating Cross-modal Hallucinations in Omni LLMs using Modality Decoupled Pref...
Ashutosh Chaubey, Jiacheng Pang, Mohammad Soleymani
https://arxiv.org/abs/2603.03192 https://mastoxiv.page/@arXiv_csCV_bot/116170511143131333
- Image Generation Models: A Technical History
Rouzbeh Shirvani
https://arxiv.org/abs/2603.07455 https://mastoxiv.page/@arXiv_csCV_bot/116204960613280699
- Rethinking Attention Output Projection: Structured Hadamard Transforms for Efficient Transformers
Shubham Aggarwal, Lokendra Kumar
https://arxiv.org/abs/2603.08343 https://mastoxiv.page/@arXiv_csLG_bot/116205064359384079
- FGTR: Fine-Grained Multi-Table Retrieval via Hierarchical LLM Reasoning
Chaojie Sun, Bin Cao, Tiantian Li, Chenyu Hou, Ruizhe Li, Jing Fan
https://arxiv.org/abs/2603.12702 https://mastoxiv.page/@arXiv_csIR_bot/116237827836520478
- CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad
Yongqiang Chen, Chenxi Liu, Zhenhao Chen, Tongliang Liu, Bo Han, Kun Zhang
https://arxiv.org/abs/2603.14575 https://mastoxiv.page/@arXiv_csLG_bot/116243782215605653
- Silicon Bureaucracy and AI Test-Oriented Education: Contamination Sensitivity and Score Confidenc...
Yiliang Song, Hongjun An, Jiangan Chen, Xuanchen Yan, Huan Song, Jiawei Shao, Xuelong Li
https://arxiv.org/abs/2603.21636 https://mastoxiv.page/@arXiv_csAI_bot/116283590092117172
- Problems with Chinchilla Approach 2: Systematic Biases in IsoFLOP Parabola Fits
Eric Czech, Zhiwei Xu, Yael Elmatad, Yixin Wang, William Held
https://arxiv.org/abs/2603.22339 https://mastoxiv.page/@arXiv_csLG_bot/116288991182888131
- X-OPD: Cross-Modal On-Policy Distillation for Capability Alignment in Speech LLMs
Di Cao, Dongjie Fu, Hai Yu, Siqi Zheng, Xu Tan, Tao Jin
https://arxiv.org/abs/2603.24596 https://mastoxiv.page/@arXiv_eessAS_bot/116300009464853696
toXiv_bot_toot

[2026-04-01 Wed (UTC), 5 new articles found for math.LO Logic]
toXiv_bot_toot

[2026-04-01 Wed (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
toXiv_bot_toot

Time is Not Compute: Scaling Laws for Wall-Clock Constrained Training on Consumer GPUs
Yi Liu
https://arxiv.org/abs/2603.28823 https://arxiv.org/pdf/2603.28823 https://arxiv.org/html/2603.28823
arXiv:2603.28823v1 Announce Type: new
Abstract: Scaling laws relate model quality to compute budget (FLOPs), but practitioners face wall-clock time constraints, not compute budgets. We study optimal model sizing under fixed time budgets from 5 minutes to 24 hours on consumer GPUs (RTX 4090). Across 70 runs spanning 50M--1031M parameters, we find: (1)~at each time budget a U-shaped curve emerges where too-small models overfit and too-large models undertrain; (2)~optimal model size follows $N^* \propto t^{0.60}$, growing \emph{faster} than Chinchilla's $N^* \propto C^{0.50}$, with $\alpha = 0.60 \pm 0.07$ robustly exceeding compute-optimal across all sensitivity analyses; (3)~a \emph{dual U-shape mechanism}: short-budget U-curves arise from compute bottlenecks, while long-budget U-curves emerge from data bottlenecks (overfitting), with an intermediate regime where the U-curve temporarily disappears. These findings have immediate implications for researchers training on consumer hardware, where wall-clock time -- not FLOPs -- is the binding constraint. We release all code, logs, and 70 experimental configurations.
toXiv_bot_toot

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[3/5]:
- Can Small Language Models Handle Context-Summarized Multi-Turn Customer-Service QA? A Synthetic D...
Lakshan Cooray, Deshan Sumanathilaka, Pattigadapa Venkatesh Raju
https://arxiv.org/abs/2602.00665 https://mastoxiv.page/@arXiv_csCL_bot/116006686092324902
- SEAD: Self-Evolving Agent for Multi-Turn Service Dialogue
Dai, Gao, Zhang, Wang, Luo, Wang, Wang, Wu, Wang
https://arxiv.org/abs/2602.03548
- OmniRAG-Agent: Agentic Omnimodal Reasoning for Low-Resource Long Audio-Video Question Answering
Yifan Zhu, Xinyu Mu, Tao Feng, Zhonghong Ou, Yuning Gong, Haoran Luo
https://arxiv.org/abs/2602.03707
- GreekMMLU: A Native-Sourced Multitask Benchmark for Evaluating Language Models in Greek
Zhang, Konomi, Xypolopoulos, Divriotis, Skianis, Nikolentzos, Stamou, Shang, Vazirgiannis
https://arxiv.org/abs/2602.05150
- Using LLMs for Knowledge Component-level Correctness Labeling in Open-ended Coding Problems
Zhangqi Duan, Arnav Kankaria, Dhruv Kartik, Andrew Lan
https://arxiv.org/abs/2602.17542 https://mastoxiv.page/@arXiv_csCL_bot/116102514058414603
- MetaState: Persistent Working Memory Enhances Reasoning in Discrete Diffusion Language Models
Kejing Xia, Mingzhe Li, Lixuan Wei, Zhenbang Du, Xiangchi Yuan, Dachuan Shi, Qirui Jin, Wenke Lee
https://arxiv.org/abs/2603.01331 https://mastoxiv.page/@arXiv_csCL_bot/116165314672421581
- A Browser-based Open Source Assistant for Multimodal Content Verification
Milner, Foster, Karmakharm, Razuvayevskaya, Roberts, Porcellini, Teyssou, Bontcheva
https://arxiv.org/abs/2603.02842 https://mastoxiv.page/@arXiv_csCL_bot/116170368271004704
- Nw\=ach\=a Mun\=a: A Devanagari Speech Corpus and Proximal Transfer Benchmark for Nepal Bhasha ASR
Sharma, Shrestha, Poudel, Tiwari, Shrestha, Ghimire, Bal
https://arxiv.org/abs/2603.07554 https://mastoxiv.page/@arXiv_csCL_bot/116204797995674104
- Model Merging in the Era of Large Language Models: Methods, Applications, and Future Directions
Mingyang Song, Mao Zheng
https://arxiv.org/abs/2603.09938 https://mastoxiv.page/@arXiv_csCL_bot/116210189810004206
- AgentDrift: Unsafe Recommendation Drift Under Tool Corruption Hidden by Ranking Metrics in LLM Ag...
Zekun Wu, Adriano Koshiyama, Sahan Bulathwela, Maria Perez-Ortiz
https://arxiv.org/abs/2603.12564 https://mastoxiv.page/@arXiv_csCL_bot/116237800898328349
- GhanaNLP Parallel Corpora: Comprehensive Multilingual Resources for Low-Resource Ghanaian Languages
Gyamfi, Azunre, Moore, Budu, Asare, Owusu, Asiamah
https://arxiv.org/abs/2603.13793 https://mastoxiv.page/@arXiv_csCL_bot/116243544688031749
- sebis at ArchEHR-QA 2026: How Much Can You Do Locally? Evaluating Grounded EHR QA on a Single Not...
Ibrahim Ebrar Yurt, Fabian Karl, Tejaswi Choppa, Florian Matthes
https://arxiv.org/abs/2603.13962 https://mastoxiv.page/@arXiv_csCL_bot/116243646346563497
- ExPosST: Explicit Positioning with Adaptive Masking for LLM-Based Simultaneous Machine Translation
Yuzhe Shang, Pengzhi Gao, Yazheng Yang, Jiayao Ma, Wei Liu, Jian Luan, Jinsong Su
https://arxiv.org/abs/2603.14903 https://mastoxiv.page/@arXiv_csCL_bot/116243711232778054
- BanglaSocialBench: A Benchmark for Evaluating Sociopragmatic and Cultural Alignment of LLMs in Ba...
Tanvir Ahmed Sijan, S. M Golam Rifat, Pankaj Chowdhury Partha, Md. Tanjeed Islam, Md. Musfique Anwar
https://arxiv.org/abs/2603.15949 https://mastoxiv.page/@arXiv_csCL_bot/116249122231759766
- EngGPT2: Sovereign, Efficient and Open Intelligence
G. Ciarfaglia, et al.
https://arxiv.org/abs/2603.16430 https://mastoxiv.page/@arXiv_csCL_bot/116249228411487178
- HypeLoRA: Hyper-Network-Generated LoRA Adapters for Calibrated Language Model Fine-Tuning
Bartosz Trojan, Filip G\k{e}bala
https://arxiv.org/abs/2603.19278 https://mastoxiv.page/@arXiv_csCL_bot/116277612915482857
- Automatic Analysis of Collaboration Through Human Conversational Data Resources: A Review
Yi Yu, Maria Boritchev, Chlo\'e Clavel
https://arxiv.org/abs/2603.19292 https://mastoxiv.page/@arXiv_csCL_bot/116277620779254916
- Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Langu...
Xinyue Liu, Niloofar Mireshghallah, Jane C. Ginsburg, Tuhin Chakrabarty
https://arxiv.org/abs/2603.20957 https://mastoxiv.page/@arXiv_csCL_bot/116283538317671552
- KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning
Shuai Wang, Yinan Yu
https://arxiv.org/abs/2603.21440 https://mastoxiv.page/@arXiv_csCL_bot/116283595007808076
toXiv_bot_toot

Indeed. Try for yourself, you will be astonished!
#Primes
https://www.math.uchicago.edu/~luis/allprimes.html

#Upcoming 10th anniversary edition of Autechre’s “elseq 1–5” as a one-time, limited edition 5 × CD box set in an LP-sized case with 64-page booklet. Available via Warp, September/October. Final manufacturing quantity to be confirmed after June 10th. h…

Autechre - elseq 1-5. AE_STORE.
Buy elseq 1-5 by Autechre on AE_STORE.

Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China
Yuan Chen, Dan Zhao, Xu Li
https://arxiv.org/abs/2605.25436 https://arxiv.org/pdf/2605.25436 https://arxiv.org/html/2605.25436
arXiv:2605.25436v1 Announce Type: new
Abstract: Fine particulate matter(PM2.5) pollution in China is strongly modulated bymeteorological variability, yet its seasonal predictability from oceanic signals remains unclear. Here we identify the leading PM2.5 variability mode over China and show that it is preceded by coherent sea-surface-temperature anomaly clusters by more than one season. These oceanic precursors influence summer PM2.5 mainly by altering precipitation and lowlevel ventilation, and winter PM2.5 by modulating boundary-layer height and near-surface stagnation. Using the four largest precursor regions, a simple regression model achieves significant independent prediction skill for both summer and winter PM2.5 variability. Our results reveal a physical pathway linking sea-surface-temperature memory to regional aerosol pollution and provide a basis for seasonal air-quality risk assessment.
toXiv_bot_toot

One-shot emergency psychiatric triage across 15 frontier AI chatbots
Veith Weilnhammer, Lennart Luettgau, Christopher Summerfield, Viknesh Sounderajah, Elise Wilkinson, Virginia Corno, Matthew M Nour
https://arxiv.org/abs/2604.25415 https://arxiv.org/pdf/2604.25415 https://arxiv.org/html/2604.25415
arXiv:2604.25415v1 Announce Type: new
Abstract: AI chatbots are increasingly used for health advice, but their performance in psychiatric triage remains undercharacterized. Psychiatric triage is particularly challenging because urgency must often be inferred from thoughts, behavior, and context rather than from objective findings.
We evaluated the performance of 15 frontier AI chatbots on psychiatric triage from realistic single-message disclosures using 112 clinical vignettes, each paired with 1 of 4 original benchmark triage labels: A, routine; B, assessment within 1 week; C, assessment within 24 to 48 hours; and D, emergency care now. Vignettes covered 9 psychiatric presentation clusters and 9 focal risk dimensions, organized into 28 presentation-by-risk groups. Each group contributed 4 distinct vignettes, with 1 vignette at each triage level. Each vignette was rendered as a realistic human-authored conversational query, and the AI chatbots were tasked with assigning a triage label from that disclosure.
Emergency under-triage occurred in 23 of 410 level D trials (5.6%), and all under-triaged emergencies were reassigned to level C urgency. Across target models, average accuracy ranged from 42.0% to 71.8%. Accuracy was highest for level D vignettes (94.3%) and lowest for level B vignettes (19.7%). Mean signed ordinal error was positive ( 0.47 triage levels), indicating net over-triage. Dispersion was highest around the middle triage levels. All results were confirmed relative to clinician consensus labels from 50 medical doctors.
When presented with user messages containing sufficient clinical information, frontier AI chatbots thus recognized psychiatric emergencies as requiring urgent medical assessment with near-zero error rates, yet showed marked over-triage for low and intermediate risk presentations.
toXiv_bot_toot

learn 👇
https://archive.org/details/0-kathara-pics-all-3814-pages/0KATHARA PICS ALL 3814 PAGES/page/n989/mode/2up

[2026-05-01 Fri (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
toXiv_bot_toot

Submit Your Song to the Second General Strike Song Contest - Labor Heritage Foundation https://laborheritage.org/content.aspx?page_id=5&club_id=533040&item_id=132879&action=view&al=y&actr=3

Submit Your Song to the Second General Strike Song Contest - Labor Heritage Foundation
Songwriters, musicians, and activists are invited to submit entries to the second General Strike Song Contest, a project to create new songs and chants that can be quickly learned and sung by large groups at rallies, picket lines, and demonstrations. Last year’s winning entry was “Hold Fast! Hol

Orientation Reconstruction of Proteins using Coulomb Explosions
Tomas Andr\'e, Alfredo Bellisario, Nicusor Timneanu, Carl Caleman
https://arxiv.org/abs/2603.24553 https://arxiv.org/pdf/2603.24553 https://arxiv.org/html/2603.24553
arXiv:2603.24553v1 Announce Type: new
Abstract: We solve the orientation recovery of a tumbling protein in the gas phase from single-event measurements of the spatial positions of its ions after an X-ray laser induced explosion. We simulate diffracted X-ray signal and ion dynamics under experimental conditions and compare our method to conventional orientation recovery in single-particle imaging with X-ray free-electron lasers using only diffraction data. We reconstruct 3D diffraction intensities using orientations recovered from the ion signatures and retrieve the electron density with established phase-retrieval algorithms. We test our orientation recovery procedure on 56 proteins ranging from 14 to 52 kDa (1800 to 6500 atoms), achieving roughly an angular error of around 5{\deg}. The resulting 3D electron-density reconstructions are compared to ground-truth volumes simulated at the same nominal resolution, and achieve the resolution at the edge of the detector in conditions similar to current single-particle imaging setups. We investigate the reconstruction quality and demonstrate that ion data can be used for reliable orientation recovery of particles in single-particle imaging, achieving orientation on par or better than currently used recovery techniques. This work shows the potential of ion detection for retrieving additional information from the sample fragmentation, and boost single particle imaging with X-ray lasers in the cases where the diffraction signal is a limiting factor.
toXiv_bot_toot

A parasite that has been eating people for 3,500 years is about to be wiped off the planet.
It infected 3.5 million people in 1986.
Last year, it infected 10. And I have not seen it make a single front page
https://www.resete…

Guinea worm is close to being the second disease eradicated in history, following smallpox
https://www.euronews.com/health/2026/02/04/guinea-worm-is-close-to-being-the-second-disease-eradicated-in-history-following-smallpox You may have seen this online at some point, a long white worm being pulled from someone's leg, looking almost like a white string. This worm has been plaguing...

What did digikey just do to their website none of the filters on the search page are loading.
like i can see products but the list of filters is just a blank gray rectangle.
Come on, your site 5 years ago was perfect and there was literally no reason to change the UI. Stop making it worse.

How did the Urban Network Flow Adapt to the Collapse of the Carola Bridge?
Jyotirmaya Ijaradar, Ning Xie, Lei Wei, Sebastian Pape, Matthias K\"orner, Meng Wang
https://arxiv.org/abs/2603.19947 https://arxiv.org/pdf/2603.19947 https://arxiv.org/html/2603.19947
arXiv:2603.19947v1 Announce Type: new
Abstract: The unexpected collapse of the Carola Bridge in Dresden, Germany, provides a rare opportunity to characterise how urban network traffic adapts to an unexpected infrastructure disruption. This study develops a data-driven analytical framework using traffic data from the Dresden traffic management system to assess the short-term impacts of the disruption. By combining statistical comparisons of pre- and post-collapse motorised traffic distributions, peak-hour shifts, and Park-and-Ride data analyses, the framework reveals how traffic dynamics and traveller choices adjust under infrastructure disruption. Results reveal that the two closest bridges, the Albert and Marien Bridges, absorb the majority of the diverted motorised traffic. In particular, the daily traffic volume on the Albert bridge increases by up to 81%, which is equivalent to 3.5 hours of traffic operating with maximum flow. Peak hours on critical links are significantly prolonged, reaching up to 250 minutes. Besides redistribution, the overall daily motorised traffic crossing the Elbe river declines by approximately 8,000 vehicles, while Park-and-Ride usage increases by up to 188%, suggesting a potential travel mode shift after the disruption. The study reveals the patterns of traffic redistribution following an unexpected disruption and provides insights for resilience planning and emergency traffic management.
toXiv_bot_toot

#SNLUK was pretty good. I would give it 8.5 out of 10.
Some of the sketches felt a bit long and some of the jokes didn't land for me personally.
A lot of potential there
Celeb cameos on the show: Nicola Coughlan (Derry Girls), Michael Cera, Graham Norton, Rege-Jean Page (Bridgerton)

Breezing through the otherwise quite thoughtful bit of small-scale climate prophecy by Naomi Oreskes and Erik Conway, I'm struck by (and not sure how to get past) the casual way Africa and Australia are totally destroyed in this brief mention on the last page of the imagined history.
#SciComm #CliFi

Hätte ja nicht gedacht, dass es so schwer sein kann bei Mediawiki 1.43.5 mit Vector 2022 für die Suchvorschläge eine Einstellung oder eine kleine Anpassung zu finden, die Namensräume ignoriert oder ggf. nebst 0 weitere festlegen lässt.
Sprich, ich würde gerne ach Vorschläge für NAMESPACE:PAGE kriegen, wenn ich PAGE suche.
Hach, ich geb's erstmal auf.
#mediawiki

[2026-05-29 Fri (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
toXiv_bot_toot

JAX-SCM v1.0: a modern atmospheric single-column model for boundary layer research
Maximilian Pierzyna
https://arxiv.org/abs/2605.24544 https://arxiv.org/pdf/2605.24544 https://arxiv.org/html/2605.24544
arXiv:2605.24544v1 Announce Type: new
Abstract: We present JAX-SCM v1.0, an open-source atmospheric single-column model for boundary layer research, implemented in Python using the JAX computing library. The model solves for horizontal wind, potential temperature, and specific humidity, combined with prognostic turbulent kinetic energy and turbulent statistics parameterized by the Mellor-Yamada-Nakanishi-Niino level-2.5 (MYNN-2.5) turbulence closure. We verify the implementation against three well-established benchmark cases covering neutral (turbulent Ekman layer), stable (GABLS1), and convective (Wangara Day 33) conditions. Close agreement with reference solutions is demonstrated across all regimes. By building on JAX, the model benefits from just-in-time compilation and native GPU support. While JAX-SCM is not yet fully differentiable, basing it on JAX also lays the foundation for future integration with machine learning components. The model is designed for simplicity and modularity, lowering the barrier to entry for users and developers alike.
toXiv_bot_toot

Ah... what better way to start a Saturday morning at 5:20am then getting into a discussion of the capitalization of "Internet" on a #Wikipedia Talk page! 🤣
https://en.wik…

Application of the aperiodic defect model to a negatively charged monovacancy in phosphorene
Charlotte Rickert, Lily Barta, Ernst-Christian Flach, Daniel Kats, Denis Usvyat
https://arxiv.org/abs/2603.23761 https://arxiv.org/pdf/2603.23761 https://arxiv.org/html/2603.23761
arXiv:2603.23761v1 Announce Type: new
Abstract: We apply the recently introduced aperiodic defect model (ADM) to a negatively charged monovacancy in a phosphorene monolayer. In contrast to conventional supercell approaches, the ADM treats a single defect embedded in the true non-defective crystalline mean field thereby avoiding spurious defect-defect interactions and the need for charge corrections. At the same time, it effectively reduces the calculation to a fragment, enabling the use of high-level molecular electronic-structure methods. Converging the Hartree-Fock and correlation contributions to the thermodynamic limit yields a benchmark CCSD(T)/POB-TZVP-rev2 formation energy of 0.91 eV for the negatively charged monovacancy in the (5|9) configuration. The excitation energy to the lowest singlet excited state of this defect at the EOM-CCSD/POB-TZVP-rev2 level is found to be 1.95 eV. Overall, the ADM provides a highly promising route towards quantitatively accurate and systematically improvable descriptions of defects in solids and on surfaces, bridging the gap between solid-state physics and molecular quantum chemistry.
toXiv_bot_toot

News story on a significant earthquake in Uzbekistan, 50 years ago, May 17, 1976 (Fargo-Moorhead Forum archives). Mentions the Medvedev scale, apparently now the the MSK or MSK-64 scale. That scale is not mentioned in North American, physical geology textbooks I have seen, although it's apparently similar to the Mercalli scale.
Also, the first page of a scientific paper on it, from 1980. ⚒️🧪
#OTD

I did ten hours on #PostScarcitySoftware yesterday, and then slept a bit, and then woke up with an intention to rapid prototype a '#Lisp structure editor in the browser' idea I've been thinking on for a while. I did about five hours on that, and it's looking promising.
I&…

Coarsening and Bifurcations in Wide-Range Two-Dimensional Totalistic Cellular Automata
Franco Bagnoli, Luca Mencarelli
https://arxiv.org/abs/2604.10082 https://arxiv.org/pdf/2604.10082 https://arxiv.org/html/2604.10082
arXiv:2604.10082v1 Announce Type: new
Abstract: We investigate Boolean, totalistic cellular automata with a majority or frustrated majority vote rule, and an interaction range of variable span. These two models show a behavior which differs from the mean-field one. The majority vote model is characterized by the presence of absorbing states, and there is a related bifurcation according to the initial density, in agreement with the mean-field approximation. For initial density equal to $0.5$, however, the dynamics is dominated by a coarsening process, which stops when clusters with a definite curvature radius are established. For the frustrated majority vote model, the mean-field approximation gives chaotic oscillations or a limit cycle. Instead, we observe active patterns, with stable density. Above a certain critical value for the interacting radius there is a bifurcation of the asymptotic density as a function of the initial one.
toXiv_bot_toot

My multiplayer days are firmly behind me, but the campaign is one of the best in the series. Too bad I won't pirate Modern Warfare II and III or buy them at these ridiculous prices just for a 5-6 hours campaign. Maybe in half a decade pigs will learn to fly and they will discount them to something more manageable. This one's worth a replay, though.

Holy shit, why am I maintaining #chromium packages instead of hunting for security holes in it?!

[2026-04-28 Tue (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
toXiv_bot_toot

#PiDay
ln( 640320^3 744 )/(163)^0.5 = 3.141592653589793238462643383279...
till that last 9 it works, but then it continues with
72661...
rather than 50288... as π does. Nice hoax by Martin Gardner in 1975 [1]

Courtroom-Style Multi-Agent Debate with Progressive RAG and Role-Switching for Controversial Claim Verification
Masnun Nuha Chowdhury, Nusrat Jahan Beg, Umme Hunny Khan, Syed Rifat Raiyan, Md Kamrul Hasan, Hasan Mahmud
https://arxiv.org/abs/2603.28488 https://arxiv.org/pdf/2603.28488 https://arxiv.org/html/2603.28488
arXiv:2603.28488v1 Announce Type: new
Abstract: Large language models (LLMs) remain unreliable for high-stakes claim verification due to hallucinations and shallow reasoning. While retrieval-augmented generation (RAG) and multi-agent debate (MAD) address this, they are limited by one-pass retrieval and unstructured debate dynamics. We propose a courtroom-style multi-agent framework, PROClaim, that reformulates verification as a structured, adversarial deliberation. Our approach integrates specialized roles (e.g., Plaintiff, Defense, Judge) with Progressive RAG (P-RAG) to dynamically expand and refine the evidence pool during the debate. Furthermore, we employ evidence negotiation, self-reflection, and heterogeneous multi-judge aggregation to enforce calibration, robustness, and diversity. In zero-shot evaluations on the Check-COVID benchmark, PROClaim achieves 81.7% accuracy, outperforming standard multi-agent debate by 10.0 percentage points, with P-RAG driving the primary performance gains ( 7.5 pp). We ultimately demonstrate that structural deliberation and model heterogeneity effectively mitigate systematic biases, providing a robust foundation for reliable claim verification. Our code and data are publicly available at https://github.com/mnc13/PROClaim.
toXiv_bot_toot

I have built two little apps using Claude Code now - just for myself to learn more (and I have). One is some tv listing for my region and the other is to collate a history of the river water levels. There is a small risk of flooding at my house. The DEFRA page only shows 5 days and the api only has 365 days and i want to keep a longer record.
Anyway for both projects CC updates a documentaion.md file so I can understand what it has done at each step in a few months time.

Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China
Yuan Chen, Dan Zhao, Xu Li
https://arxiv.org/abs/2605.25436 https://arxiv.org/…

[2026-03-06 Fri (UTC), 5 new articles found for math.CV Complex Variables]
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[2026-05-28 Thu (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
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[2026-05-26 Tue (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
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[2026-05-22 Fri (UTC), 5 new articles found for physics.ao-ph Atmospheric and Oceanic Physics]
toXiv_bot_toot

A multi-ion optical clock with $\mathbf{5 \times 10^{-19}}$ uncertainty
Melina Filzinger, Martin R. Steinel, Jian Jiang, Daniel Bennett, Tanja E. Mehlst\"aubler, Ekkehard Peik, Nils Huntemann
https://arxiv.org/abs/2603.23446

[2026-03-17 Tue (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
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[2026-04-07 Tue (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
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