Uncertainty trace profiles from LM reasoning traces predict correct final answers with AUROC up to 0.807 and enable early error detection using only initial tokens.
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Multi-LLM committees amplify small input perturbations into divergent deliberation trajectories and decisions under deterministic conditions.
Analysis of 955 Korean decision conversations reveals people favor satisficing and interactional strategies over optimization, with common heuristics aiding exploration flow while rare rule-based ones drive resolution.
citing papers explorer
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Tracing Uncertainty in Language Model "Reasoning"
Uncertainty trace profiles from LM reasoning traces predict correct final answers with AUROC up to 0.807 and enable early error detection using only initial tokens.
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Collective AI can amplify tiny perturbations into divergent decisions
Multi-LLM committees amplify small input perturbations into divergent deliberation trajectories and decisions under deterministic conditions.
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Analyzing Human Heuristics and Strategies in Everyday Decision-Making Conversations for Conversational AI Design
Analysis of 955 Korean decision conversations reveals people favor satisficing and interactional strategies over optimization, with common heuristics aiding exploration flow while rare rule-based ones drive resolution.