Arman Cohan
6 indexed papers
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The paper introduces a novel framework to quantify faithful confidence expression (FC) in Large Reasoning Models (LRMs), finding that FC remains a significant and challenging reliability target for these models.
The paper introduces a novel framework to quantify faithful confidence expression (FC) in Large Reasoning Models (LRMs), finding that FC remains a significant and challenging reliability target for these models.
The paper introduces Every Eval Ever, a shared schema and community-crowdsourced repository for AI evaluation results to standardize and compare AI evaluations.
This paper introduces two novel mechanisms, reinforcement learning with metacognitive feedback (RLMF) and metacognitive data selection, to enhance language model metacognition and achieve faithful calibration.
The paper evaluates the gap between LLM-generated research ideas and human research ideas by building an evaluation framework and observing a distributional gap.
The paper introduces IdeaAnchor, a paradigm for training LLMs to perform research ideation using structured specifications.
Papers
IdeaAnchor: Teaching LLMs to Turn Literature into Research Ideas
Ziyu Chen, Yilun Zhao, Jiashuo Sun, Yiling Ma +2 more
The paper introduces IdeaAnchor, a paradigm for training LLMs to perform research ideation using structured specifications.