Alignment, bias, regulation, and responsible AI
![[2512.21106] Semantic Refinement with LLMs for Graph Representations](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2512.21106: Semantic Refinement with LLMs for Graph Representations
Abstract page for arXiv paper 2511.22294: Structure is Supervision: Multiview Masked Autoencoders for Radiology
Abstract page for arXiv paper 2511.18123: Bias Is a Subspace, Not a Coordinate: A Geometric Rethinking of Post-hoc Debiasing in Vision-La...
The paper presents ARLArena, a framework designed to enhance stability in agentic reinforcement learning (ARL) by providing a systematic ...
The paper explores the limitations of self-correction in Large Language Models (LLMs) regarding semantic sensitive information, introduci...
This article provides a comprehensive overview of soft set theory and its various extensions, highlighting key definitions, constructions...
The Reddit discussion seeks insights on Neural Tangent Kernel (NTK) in relation to lazy and rich learning regimes, focusing on practical ...
The article features an in-depth interview with Anthropic co-founder discussing the potential impact of AI agents on the economy, explori...
Sentinel Gateway addresses the challenge of instruction provenance in AI agents by ensuring only user-signed prompts are treated as execu...
The White House is urging major AI companies to absorb rising electricity costs linked to their data centers. Most firms, including Micro...
Discussion on whether ICLR is suspending Spotlights this year, with concerns over communication and potential impacts from OpenReview leaks.
Public opposition to AI infrastructure is rising, leading to legislative proposals for moratoriums on new data center constructions acros...
The article discusses the limitations of current benchmarks for measuring human-like intelligence in AI, highlighting Francois Chollet's ...
A Pew Research Center report reveals that 12% of U.S. teens use AI chatbots for emotional support, raising concerns among mental health p...
This discussion explores methods to identify papers that are predominantly generated by language models like ChatGPT, focusing on detecti...
The article discusses the Anthropic-Pentagon situation, framing it as a governance-layer conflict in AI rather than a political debate, f...
The article discusses the impending deadline set by the Pentagon for Anthropic, raising questions about their potential involvement in mi...
Anthropic executives suggest that their AI model, Claude, may possess a form of consciousness, sparking debates about the implications of...
This article presents a comprehensive study on prefill attacks in open-weight LLMs, revealing a near-perfect success rate across 50 model...
The article discusses the contradictory narratives surrounding AI in various industries, highlighting how stakeholders often misrepresent...
IBM's 2026 X-Force Threat Intelligence Index reveals a 44% rise in cyberattacks exploiting basic security gaps, driven by AI tools that e...
This article evaluates the uncertainty calibration of multi-label bird sound classifiers, highlighting the challenges and improvements in...
This paper analyzes the impact of watermarking on the alignment of language models, revealing significant shifts in model behavior and pr...
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