ReasoningFlow: Semantic Structure of Complex Reasoning Traces
arXiv:2506.02532
Abstract
Large reasoning models (LRMs) generate complex reasoning traces with planning, reflection, verification, and backtracking. In this work, we introduce ReasoningFlow, a unified schema for analyzing the semantic structures of these complex traces. ReasoningFlow parses traces into directed acyclic graphs, enabling the characterization of distinct reasoning patterns as subgraph structures. This human-interpretable representation offers promising applications in understanding, evaluating, and enhancing the reasoning processes of LRMs.
10 pages, 6 figures. ArgMining 2025 Workshop (Non-archival) @ ACL 2025