Algorithms based on the least core approximate stable credit assignments for AI-generated content using orders of magnitude fewer LLM calls than alternatives.
Attribot: A bag of tricks for efficiently approximating leave-one-out context attribution
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RREDCoT approximates segment-level reward redistribution for CoT traces by querying the model itself, offering a lower-cost alternative to Monte Carlo credit assignment in reasoning-model RL.
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In-Context Credit Assignment via the Core
Algorithms based on the least core approximate stable credit assignments for AI-generated content using orders of magnitude fewer LLM calls than alternatives.
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RREDCoT: Segment-Level Reward Redistribution for Reasoning Models
RREDCoT approximates segment-level reward redistribution for CoT traces by querying the model itself, offering a lower-cost alternative to Monte Carlo credit assignment in reasoning-model RL.