ProRAC: A Neuro-symbolic Method for Reasoning about Actions with LLM-based Progression

• URL: http://arxiv.org/abs/2511.15069v1
• Date: Wed, 19 Nov 2025 03:20:06 GMT
• Title: ProRAC: A Neuro-symbolic Method for Reasoning about Actions with LLM-based Progression
• Abstract summary: We propose ProRAC, a neuro-symbolic framework to tackle RAC problems.<n>ProRAC extracts RAC elements including actions and questions from the problem.<n>We evaluate ProRAC on several RAC benchmarks, and the results demonstrate that our approach achieves strong performance.
• Score: 3.7838089347652244
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we propose ProRAC (Progression-based Reasoning about Actions and Change), a neuro-symbolic framework that leverages LLMs to tackle RAC problems. ProRAC extracts fundamental RAC elements including actions and questions from the problem, progressively executes each action to derive the final state, and then evaluates the query against the progressed state to arrive at an answer. We evaluate ProRAC on several RAC benchmarks, and the results demonstrate that our approach achieves strong performance across different benchmarks, domains, LLM backbones, and types of RAC tasks.

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