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State Representation and Termination for Recursive Reasoning Systems

arXiv 2605.06690 ↗First posted 2 May 2026cs.AI cs.CL cs.LGcited by 0

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Abstract (arXiv)

Recursive reasoning systems alternate between acquiring new evidence and refining an accumulated understanding. Two design choices are typically left implicit: how to represent the evolving reasoning state, and when to stop iterating. This paper addresses both. We represent the reasoning state as an epistemic state graph encoding extracted claims, evidential relations, open questions, and confidence weights. We define the order-gap as the distance between the states reached by expand-then-consolidate versus consolidate-then-expand; a small order-gap suggests that the two orderings agree and further iteration is unlikely to help. Our main result gives a necessary and sufficient condition for the linearised order-gap to be non-degenerate near the fixed point, showing when the criterion is informative rather than algebraically vacuous. This is a local condition, not a global convergence guarantee. We apply the framework to recursive reasoning systems and sketch its application to agent loops, tree-of-thought reasoning, theorem proving, and continual learning.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 17 references that are in the map. First posted on arXiv 2 May 2026.

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References · 12

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2016Overcoming catastrophic forgetting in neural networkscited by 4,787
  4. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,455
  5. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  6. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,211
  7. 2022Language Models (Mostly) Know What They Knowcited by 1,856
  8. 2023Large Language Models Cannot Self-Correct Reasoning Yetcited by 1,017
  9. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 923
  10. 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 886
  11. 2022HyperTree Proof Search for Neural Theorem Provingcited by 197
  12. 2025Recursive Language Modelscited by 104

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  1. 2026Recursive Models for Long-Horizon Reasoning
  2. 2025Reasoning Systems as Structured Processes: Foundations, Failures, and Formal Criteria
  3. 2026Recursive Agentic Reasoning
  4. 2026Mind the Perspective: Let's Reason Recursively for Theory of Mind
  5. 2026Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents
  6. 2026The Reasoning Trap: An Information-Theoretic Bound on Closed-System Multi-Step LLM Reasoning
  7. 2025Dialogue-based Explanations for Logical Reasoning using Structured Argumentation
  8. 2026Chained Recursive Language Models for Multi-Iteration Reasoning