English

ReasoningFlow: Semantic Structure of Complex Reasoning Traces

Computation and Language 2025-06-04 v1

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.

Keywords

Cite

@article{arxiv.2506.02532,
  title  = {ReasoningFlow: Semantic Structure of Complex Reasoning Traces},
  author = {Jinu Lee and Sagnik Mukherjee and Dilek Hakkani-Tur and Julia Hockenmaier},
  journal= {arXiv preprint arXiv:2506.02532},
  year   = {2025}
}

Comments

10 pages, 6 figures. ArgMining 2025 Workshop (Non-archival) @ ACL 2025

R2 v1 2026-07-01T02:56:07.806Z