mlsanityData to 7 Oct 2026

Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models

arXiv 2601.11340 ↗First posted 16 Jan 2026cs.CLcited by 7

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

Abstract (arXiv)

Chain-of-Thought reasoning has significantly enhanced the problem-solving capabilities of Large Language Models. Unfortunately, current models generate reasoning steps sequentially without foresight, often becoming trapped in suboptimal reasoning paths with redundant steps. In contrast, we introduce Neural Chain-of-Thought Search (NCoTS), a framework that reformulates reasoning as a dynamic search for the optimal thinking strategy. By quantitatively characterizing the solution space, we reveal the existence of sparse superior reasoning paths that are simultaneously more accurate and concise than standard outputs. Our method actively navigates towards these paths by evaluating candidate reasoning operators using a dual-factor heuristic that optimizes for both correctness and computational cost. Consequently, NCoTS achieves a Pareto improvement across diverse reasoning benchmarks, boosting accuracy by over 3.5% while reducing generation length by over 22%. Our code and data are available at https://github.com/MilkThink-Lab/Neural-CoT-Search.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 206 of its 245 references that are in the map. First posted on arXiv 16 Jan 2026.

Builds on

206 of 245 references.

Closest ancestors · 19

Same direction, newest first

  1. 2025Revisiting Chain-of-Thought Prompting: Zero-shot Can Be Stronger than Few-shot17 Jun
  2. 2025Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning11 Jun
  3. 2025Answer Convergence as a Signal for Early Stopping in Reasoning3 Jun
  4. 2025DRP: Distilled Reasoning Pruning with Skill-aware Step Decomposition for Efficient Large Reasoning Models20 May
  5. 2025Fractured Chain-of-Thought Reasoning19 May
  6. 2025Ada-R1: Hybrid-CoT via Bi-Level Adaptive Reasoning Optimization30 Apr
  7. 2025Weight-of-Thought Reasoning: Exploring Neural Network Weights for Enhanced LLM Reasoning14 Apr
  8. 2025Think When You Need: Self-Adaptive Chain-of-Thought Learning4 Apr
  9. 2025Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models12 Mar
  10. 2025Chain of Draft: Thinking Faster by Writing Less25 Feb
  11. 2025Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models18 Feb
  12. 2025Small Models Struggle to Learn from Strong Reasoners17 Feb
7 more
  1. 2025When More is Less: Understanding Chain-of-Thought Length in LLMs11 Feb
  2. 2024Unlocking the Capabilities of Thought: A Reasoning Boundary Framework to Quantify and Optimize Chain-of-Thought8 Oct
  3. 2024Distilling System 2 into System 18 Jul
  4. 2024The Impact of Reasoning Step Length on Large Language Models10 Jan
  5. 2023Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation7 Nov
  6. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Models21 Mar
  7. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Models28 Jan

Other references · 187

  1. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  2. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  3. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  4. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  5. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,203
  6. 2024Qwen2.5 Technical Reportcited by 4,713
  7. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,710
  8. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  9. 2023GPQA: A Graduate-Level Google-Proof Q&A Benchmarkcited by 2,748
  10. 2018DARTS: Differentiable Architecture Searchcited by 1,782
  11. 2016Neural Architecture Search with Reinforcement Learningcited by 1,489
  12. 2024OpenAI o1 System Cardcited by 1,220
38 more
  1. 2025Kimi k1.5: Scaling Reinforcement Learning with LLMscited by 1,193
  2. 2017Learning Transferable Architectures for Scalable Image Recognitioncited by 1,097
  3. 2024SimPO: Simple Preference Optimization with a Reference-Free Rewardcited by 951
  4. 2018MnasNet: Platform-Aware Neural Architecture Search for Mobilecited by 937
  5. 2018Regularized Evolution for Image Classifier Architecture Searchcited by 902
  6. 2023Reasoning with Language Model is Planning with World Modelcited by 846
  7. 2018Efficient Neural Architecture Search via Parameter Sharingcited by 831
  8. 2016Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimizationcited by 688
  9. 2018ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardwarecited by 666
  10. 2023Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Modelscited by 551
  11. 2025Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoningcited by 540
  12. 2025Stop Overthinking: A Survey on Efficient Reasoning for Large Language Modelscited by 456
  13. 2025L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learningcited by 381
  14. 2024ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Searchcited by 338
  15. 2025Demystifying Long Chain-of-Thought Reasoning in LLMscited by 323
  16. 2025From System 1 to System 2: A Survey of Reasoning Large Language Modelscited by 319
  17. 2025The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexitycited by 298
  18. 2023Alphazero-like Tree-Search can Guide Large Language Model Decoding and Trainingcited by 291
  19. 2025Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Modelscited by 291
  20. 2025O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruningcited by 278
  21. 2025TokenSkip: Controllable Chain-of-Thought Compression in LLMscited by 246
  22. 2024Token-Budget-Aware LLM Reasoningcited by 242
  23. 2025Training Language Models to Reason Efficientlycited by 242
  24. 2023Large Language Models as Commonsense Knowledge for Large-Scale Task Planningcited by 231
  25. 2023Large Language Model Guided Tree-of-Thoughtcited by 218
  26. 2025Dynamic Early Exit in Reasoning Modelscited by 217
  27. 2023Self-Evaluation Guided Beam Search for Reasoningcited by 195
  28. 2017Hierarchical Representations for Efficient Architecture Searchcited by 188
  29. 2025ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learningcited by 187
  30. 2025Reasoning Models Can Be Effective Without Thinkingcited by 182
  31. 2025A Survey of Reinforcement Learning for Large Reasoning Modelscited by 175
  32. 2025CoT-Valve: Length-Compressible Chain-of-Thought Tuningcited by 167
  33. 2025DAST: Difficulty-Adaptive Slow-Thinking for Large Reasoning Modelscited by 154
  34. 2024Tree Search for Language Model Agentscited by 148
  35. 2025AdaptThink: Reasoning Models Can Learn When to Thinkcited by 141
  36. 2024Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solverscited by 137
  37. 2025A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyondcited by 131
  38. 2025Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuningcited by 121

50 most cited of 187 All 187 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 7.

7 papers.

  1. 2026ATTNPO: Attention-Guided Process Supervision for Efficient Reasoningcited by 9
  2. 2026One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinementcited by 6
  3. 2026ActorMind: Emulating Human Actor Reasoning for Speech Role-Playingcited by 4
  4. 2026Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoningcited by 1
  5. 2026BLUE: Toward Better Language Use in Efficient Vision-Language-Action Models for Autonomous Drivingcited by 1
  6. 2026LayerTracer: A Joint Task-Particle and Vulnerable-Layer Analysis framework for Arbitrary Large Language Model Architecturescited by 0
  7. 2026Escaping Redundant Reasoning: Structure-Aware Search for Inference-Time LLMscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation
  2. 2024Chain-of-Thought in Large Language Models: Decoding, Projection, and Activation
  3. 2025From Reasoning to Super-Intelligence: A Search-Theoretic Perspective
  4. 2024Fine-Tuning on Diverse Reasoning Chains Drives Within-Inference CoT Refinement in LLMs
  5. 2023ThoughtSource: A central hub for large language model reasoning data
  6. 2025Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning
  7. 2025Early Stopping Chain-of-thoughts in Large Language Models
  8. 2023DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models