Reflection-Bench: Evaluating Epistemic Agency in Large Language Models

• URL: http://arxiv.org/abs/2410.16270v3
• Date: Wed, 04 Jun 2025 11:45:19 GMT
• Title: Reflection-Bench: Evaluating Epistemic Agency in Large Language Models
• Authors: Lingyu Li, Yixu Wang, Haiquan Zhao, Shuqi Kong, Yan Teng, Chunbo Li, Yingchun Wang,
• Abstract summary: Epistemic agency is the ability to flexibly construct, adapt, and monitor beliefs about dynamic environments.<n>We propose Reflection-Bench, a benchmark consisting of seven tasks with long-term relevance and minimization of data leakage.<n>Our findings suggest several promising research directions, including enhancing core cognitive functions, improving cross-functional coordination, and developing adaptive processing mechanisms.
• Score: 10.801745760525838
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: With large language models (LLMs) increasingly deployed as cognitive engines for AI agents, the reliability and effectiveness critically hinge on their intrinsic epistemic agency, which remains understudied. Epistemic agency, the ability to flexibly construct, adapt, and monitor beliefs about dynamic environments, represents a base-model-level capacity independent of specific tools, modules, or applications. We characterize the holistic process underlying epistemic agency, which unfolds in seven interrelated dimensions: prediction, decision-making, perception, memory, counterfactual thinking, belief updating, and meta-reflection. Correspondingly, we propose Reflection-Bench, a cognitive-psychology-inspired benchmark consisting of seven tasks with long-term relevance and minimization of data leakage. Through a comprehensive evaluation of 16 models using three prompting strategies, we identify a clear three-tier performance hierarchy and significant limitations of current LLMs, particularly in meta-reflection capabilities. While state-of-the-art LLMs demonstrate rudimentary signs of epistemic agency, our findings suggest several promising research directions, including enhancing core cognitive functions, improving cross-functional coordination, and developing adaptive processing mechanisms. Our code and data are available at https://github.com/AI45Lab/ReflectionBench.

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