Alignment, bias, regulation, and responsible AI
What happens that while training an AI during pre training we make it such that if makes "misaligned behaviour" then we just reduce like ...
What happens that while training an AI during pre training we make it such that if makes "misaligned behaviour" then we just reduce like ...
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![[2602.21231] ACAR: Adaptive Complexity Routing for Multi-Model Ensembles with Auditable Decision Traces](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper presents ACAR, a framework for adaptive complexity routing in multi-model ensembles, demonstrating improved task routing accura...
The paper introduces IslamicLegalBench, a benchmark for evaluating LLMs' reasoning on Islamic law, revealing significant limitations in c...
The paper introduces EPSVec, a novel method for generating synthetic data using dataset vectors, enhancing privacy and efficiency in mach...
The paper introduces Applied Sociolinguistic AI for Community Development (ASA-CD), a paradigm that leverages AI and linguistics to addre...
This paper presents Sparse Inference-time Alignment (SIA), a novel approach to enhance alignment in large language models by intervening ...
This study explores how large language models (LLMs) exhibit inconsistent biases towards algorithmic agents and human experts in decision...
This paper presents a novel approach using Petri nets to identify infeasibilities in sequential task planning, enhancing robustness and e...
The paper presents the 2-Step Agent framework, which models the interaction between decision makers and AI decision support systems, high...
This paper presents a novel reinforcement learning approach to enhance claim verification by optimizing decomposition quality and verifie...
The paper presents fEDM+, an enhanced fuzzy ethical decision-making framework that improves explainability and validation by integrating ...
The ASIR Courage Model presents a phase-dynamic framework for understanding truth transitions in both human and AI systems, emphasizing t...
The paper explores the effectiveness of aggregating outputs from multiple AI models in compound AI systems, examining its potential to en...
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.
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