Tootfinder

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

Fabrizio Sgura will speak on 'Platform Engineering Starts at the Node: The Power of Immutable Operating Systems' as part of our Cloud Native Days track at SCaLE 23x. Full details: https://www.socallinuxexpo.org/scale/23x

"#GitHub Actions Is Slowly Killing Your Engineering Team"
#Azure over GitHub. Yes, they managed to make something worse. Much worse.

Anthropic details how it used 16 parallel Claude Opus 4.6 agents to build a Rust-based 100,000-line C compiler, incurring ~$20K in API costs over 2,000 sessions (Anthropic)
https://www.anthropic.com/engineering/building-c-compiler

Building a C compiler with a team of parallel Claudes
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

🫦 Researchers pioneer pathway to mechanical intelligence by breaking symmetry in soft composite materials
https://techxplore.com/news/2025-11-pathway-mechanical-intelligence-symmetry-soft.html

Researchers pioneer pathway to mechanical intelligence by breaking symmetry in soft composite materials
A research team has developed soft composite systems with highly programmable, asymmetric mechanical responses. By integrating "shear-jamming transitions" into compliant polymeric solids, this innovative work enhances key material functionalities essential for engineering mechano-intelligent systems—a major step toward the development of next-generation smart materials and devices.

Caitlin Kalinowski, OpenAI's head of hardware and robotic engineering, resigns citing concerns over domestic surveillance and lethal autonomous weapons systems (Sharon Goldman/Fortune)
https://fortune.com/2026/03/07/openai-…

Cryogenics and the use of superfluid helium in high-energy particle accelerators (1980-2000)
Philippe Lebrun
https://arxiv.org/abs/2602.14298 https://arxiv.org/pdf/2602.14298 https://arxiv.org/html/2602.14298
arXiv:2602.14298v1 Announce Type: new
Abstract: The period 1980-2000 saw the impressive development of applied superconductivity in high-energy particle accelerators, from single components to long strings of superconducting magnets and high-frequency acceleration cavities. Large and powerful cryogenic systems were designed ancillary to superconducting devices operating generally close to the normal boiling point of helium, but also above 4.2 K in supercritical and below 2 K in superfluid. Low-temperature operation in accelerators also involves considerations of ultra-high vacuum, limited stored energy and beam stability. We recall the rationale for cryogenics in high-energy particle accelerators and review its development over the period of interest, with reference to the main engineering domains of cryostat design and heat loads, cooling schemes, efficient power refrigeration and cryogenic fluid management. In view of its importance and novelty, a specific section is devoted to the developments that led to the LHC at CERN.
toXiv_bot_toot

When we try to formalize a neuron computationally, we don't translate biology into code—we perform a violent collapse.
https://www.ocrampal.com/what-a-neuron-teaches-us-about-computations-limits/

What a Neuron Teaches Us About Computation's Limits
Introduction: When Success Becomes a Prison Computation has been spectacularly successful. We've used it to simulate galaxies, design aircraft, predict weather patterns, and build technologies that transform civilization. The computational paradigm—breaking systems into discrete components operating on fixed timescales with predetermined coupling rules—has revolutionized physics and engineering. But

"Building a C compiler with a team of parallel Claudes"
#AI #LLM #slop #NoAI