mlsanityData to 7 Oct 2026

Zero-Shot Verification-guided Chain of Thoughts

arXiv 2501.13122 ↗First posted 21 Jan 2025cs.CL cs.AIcited by 9

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

Abstract (arXiv)

Previous works have demonstrated the effectiveness of Chain-of-Thought (COT) prompts and verifiers in guiding Large Language Models (LLMs) through the space of reasoning. However, most such studies either use a fine-tuned verifier or rely on manually handcrafted few-shot examples. In contrast, in this paper, we focus on LLM-based self-verification of self-generated reasoning steps via COT prompts in a completely zero-shot regime. To explore this setting, we design a new zero-shot prompt, which we call COT STEP, to aid zero-shot decomposition of reasoning steps and design two new zero-shot prompts for LLM-based verifiers. We evaluate the verifiers' ability to classify the correctness of reasoning chains and explore different ways to use verifier scores in guiding reasoning for various mathematical and commonsense reasoning tasks with different LLMs.

Key facts. Cited by 9 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 20 of its 57 references that are in the map. First posted on arXiv 21 Jan 2025.

Builds on

20 of 57 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024Zero-Shot Chain-of-Thought Reasoning Guided by Evolutionary Algorithms in Large Language Models8 Feb
  2. 2024Demystifying Chains, Trees, and Graphs of Thoughts25 Jan
  3. 2023Measuring Faithfulness in Chain-of-Thought Reasoning17 Jul

Other references · 17

  1. 2024The Llama 3 Herd of Modelscited by 14,192
  2. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  3. 2023Mistral 7Bcited by 3,065
  4. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  5. 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,883
  6. 2022Language Models (Mostly) Know What They Knowcited by 1,783
  7. 2023Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verificationcited by 166
  8. 2024On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Taskscited by 137
  9. 2024Self-Discover: Large Language Models Self-Compose Reasoning Structurescited by 108
  10. 2024Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planningcited by 95
  11. 2023Strategic Reasoning with Language Modelscited by 64
  12. 2024Interpretable Contrastive Monte Carlo Tree Search Reasoningcited by 62
5 more
  1. 2024TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Samplingcited by 61
  2. 2016A Simple, Fast Diverse Decoding Algorithm for Neural Generationcited by 58
  3. 2024Improving LLM Reasoning through Scaling Inference Computation with Collaborative Verificationcited by 40
  4. 2024Towards Self-Improvement of LLMs via MCTS: Leveraging Stepwise Knowledge with Curriculum Preference Learningcited by 27
  5. 2024BEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Searchcited by 13

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 5; 2026: 4.

9 papers.

  1. 2025Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Modelscited by 381
  2. 2026A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agentscited by 47
  3. 2025A Study of LLMs' Preferences for Libraries and Programming Languagescited by 20
  4. 2025Unlocking the Power of Multi-Agent LLM for Reasoning: From Lazy Agents to Deliberationcited by 11
  5. 2025In-Token Rationality Optimization: Towards Accurate and Concise LLM Reasoning via Self-Feedbackcited by 2
  6. 2026An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computingcited by 1
  7. 2026VeryTrace: Verifying Reasoning Traces through Compilable Formalism and Structured Verificationcited by 1
  8. 2025ProofSketch: Efficient Verified Reasoning for Large Language Modelscited by 0
  9. 2026Strategy Executability in Mathematical Reasoning: Leveraging Human-Model Differences for Effective Guidancecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2022Large Language Models are Zero-Shot Reasoners
  2. 2023Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
  3. 2024Chain-of-Thought Reasoning Without Prompting
  4. 2024A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration
  5. 2023An automatically discovered chain-of-thought prompt generalizes to novel models and datasets
  6. 2024Instance-adaptive Zero-shot Chain-of-Thought Prompting
  7. 2024Break the Chain: Large Language Models Can be Shortcut Reasoners
  8. 2023SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning