newsNature Machine IntelligenceTrust 88 · LabPublished 10d agoLive · 8d ago
Implicit-bias-like patterns in reasoning models
Nature Machine Intelligence, Published online: 01 September 2026; doi:10.1038/s42256-026-01300-1 Lee and Lai study bias-like processing differences in large language reasoning models and find that, for most models, processing stereotypical information takes less computational effort than processing counter-stereotypical information.
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paperSituation Perception: A Necessary Primitive to Artificial SuperintelligencepaperThink-Probe-Respond: Improving Large Language Models as Judges of Research Idea NoveltypaperFrom Plausible to Actionable: A Position on LLM Self-ExplanationspaperDo Large Language Models Hallucinate Electric Fata Morganas?paperWhen Do Explanations Help In-Context Learning? A Comparative Study of Natural Language Explanation Types and Faithfulness
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paperWhen Do Explanations Help In-Context Learning? A Comparative Study of Natural Language Explanation Types and FaithfulnesspaperTypological Feature Prediction with Large Language Models: An In-Context Learning ApproachpaperBeyond Shallow Alignment: How Post-Training Methods Determine Refusal Circuits And Steering RobustnesspaperSituation Perception: A Necessary Primitive to Artificial SuperintelligencepaperFrom Plausible to Actionable: A Position on LLM Self-ExplanationspaperDo Large Language Models Hallucinate Electric Fata Morganas?paperThink-Probe-Respond: Improving Large Language Models as Judges of Research Idea Novelty
