mlsanityData to 14 Oct 2026

Chain of Methodologies: Scaling Test Time Computation without Training

arXiv 2506.06982 ↗First posted 8 Jun 2025cs.CLcited by 0

On the map: LLM reasoning → Prompting and chain-of-thought reasoning

Abstract (arXiv)

Large Language Models (LLMs) often struggle with complex reasoning tasks due to insufficient in-depth insights in their training data, which are typically absent in publicly available documents. This paper introduces the Chain of Methodologies (CoM), an innovative and intuitive prompting framework that enhances structured thinking by integrating human methodological insights, enabling LLMs to tackle complex tasks with extended reasoning. CoM leverages the metacognitive abilities of advanced LLMs, activating systematic reasoning throught user-defined methodologies without explicit fine-tuning. Experiments show that CoM surpasses competitive baselines, demonstrating the potential of training-free prompting methods as robust solutions for complex reasoning tasks and bridging the gap toward human-level reasoning through human-like methodological insights.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 23 of its 35 references that are in the map. First posted on arXiv 8 Jun 2025.

Builds on

23 of 35 references.

Closest ancestors · 6

Same direction, newest first

  1. 2024Faithful Logical Reasoning via Symbolic Chain-of-Thought28 May
  2. 2023Boosting Language Models Reasoning with Chain-of-Knowledge Prompting10 Jun
  3. 2023Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models6 May
  4. 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks22 Nov
  5. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Models21 Mar
  6. 2022Iteratively Prompt Pre-trained Language Models for Chain of Thought16 Mar

Other references · 17

  1. 2021Training Verifiers to Solve Math Word Problemscited by 10,109
  2. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,886
  3. 2023Let's Verify Step by Stepcited by 3,789
  4. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,754
  5. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  6. 2024Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameterscited by 1,986
  7. 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,917
  8. 2024ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Toolscited by 1,121
  9. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 923
  10. 2024ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Searchcited by 344
  11. 2024Marco-o1: Towards Open Reasoning Models for Open-Ended Solutionscited by 144
  12. 2024Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solverscited by 138
5 more
  1. 2023Metacognitive Prompting Improves Understanding in Large Language Modelscited by 58
  2. 2024Disentangling Memory and Reasoning Ability in Large Language Modelscited by 44
  3. 2023Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questionscited by 19
  4. 2023IAG: Induction-Augmented Generation Framework for Answering Reasoning Questionscited by 15
  5. 2023Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Modelscited by 5

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
  2. 2025IAO Prompting: Making Knowledge Flow Explicit in LLMs through Structured Reasoning Templates
  3. 2023Eliminating Reasoning via Inferring with Planning: A New Framework to Guide LLMs' Non-linear Thinking
  4. 2024Enhancing Chain of Thought Prompting in Large Language Models via Reasoning Patterns
  5. 2025Mapping the Minds of LLMs: A Graph-Based Analysis of Reasoning LLM
  6. 2025Layered Chain-of-Thought Prompting for Multi-Agent LLM Systems: A Comprehensive Approach to Explainable Large Language Models
  7. 2025Probing Large Language Models in Reasoning and Translating Complex Linguistic Puzzles
  8. 2023Thought Propagation: An Analogical Approach to Complex Reasoning with Large Language Models