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论文精选 82arXiv

Understanding Jev-Style System One Models: Does Structure Reduce Selection Bias?· 理解 Jev-Style System One 模型

Selection bias in large language models (LLMs) can persist despite instructions to ignore presentation order or prompts that elicit reasoning. Recent efforts to reproduce Jev-style System One behavior have produced a growing family of models that predict probabilities directly over supplied candidates. Yet systematic comparisons of selection bias across Jev versions, Jev reproductions, and generative LLMs remain limited in multi-option tasks. This leaves a central question: does Jev-style decision structure reduce selection bias? We address this question with a simple test that shuffles options while keeping question and candidate content fixed. Across two Jev versions, twelve Jev reproductions, and six generative LLMs, we trace individual answers through eight presentations and compare th

领域:cs.CL作者:Mingyang Song、Mao Zheng、Zhiyuan Ma
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Quantifying Claim Smoothing by LLM Research Agents· 量化 LLM 研究代理的主张平滑

Deep research, or any use of large language models (LLMs) to read a large document collect…

领域:cs.CL作者:Tiasa Singha Roy、Manya Wadhwa、Greg Durrett
📎 arXiv🕒 10-27 01:29🔗 arxiv.org

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