mlsanityData to 14 Oct 2026

ECCoT: A Framework for Enhancing Effective Cognition via Chain of Thought in Large Language Model

arXiv 2506.19599 ↗First posted 24 Jun 2025cs.CL cs.AIcited by 0

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

Abstract (arXiv)

In the era of large-scale artificial intelligence, Large Language Models (LLMs) have made significant strides in natural language processing. However, they often lack transparency and generate unreliable outputs, raising concerns about their interpretability. To address this, the Chain of Thought (CoT) prompting method structures reasoning into step-by-step deductions. Yet, not all reasoning chains are valid, and errors can lead to unreliable conclusions. We propose ECCoT, an End-to-End Cognitive Chain of Thought Validation Framework, to evaluate and refine reasoning chains in LLMs. ECCoT integrates the Markov Random Field-Embedded Topic Model (MRF-ETM) for topic-aware CoT generation and Causal Sentence-BERT (CSBert) for causal reasoning alignment. By filtering ineffective chains using structured ordering statistics, ECCoT improves interpretability, reduces biases, and enhances the trustworthiness of LLM-based decision-making. Key contributions include the introduction of ECCoT, MRF-ETM for topic-driven CoT generation, and CSBert for causal reasoning enhancement. Code is released at: https://github.com/erwinmsmith/ECCoT.git.

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 7 of its 41 references that are in the map. First posted on arXiv 24 Jun 2025.

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7 of 41 references.

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  1. 2024Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?31 Oct
  2. 2022Automatic Chain of Thought Prompting in Large Language Models7 Oct
  3. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Models21 May

Other references · 4

  1. 2023Multimodal Chain-of-Thought Reasoning in Language Modelscited by 752
  2. 2024A Survey on Knowledge Distillation of Large Language Modelscited by 284
  3. 2022PINTO: Faithful Language Reasoning Using Prompt-Generated Rationalescited by 56
  4. 2023FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answeringcited by 51

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  1. 2025Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning
  2. 2024Strategic Chain-of-Thought: Guiding Accurate Reasoning in LLMs through Strategy Elicitation
  3. 2024Fine-Tuning on Diverse Reasoning Chains Drives Within-Inference CoT Refinement in LLMs
  4. 2024On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models
  5. 2025CoT-RAG: Integrating Chain of Thought and Retrieval-Augmented Generation to Enhance Reasoning in Large Language Models
  6. 2026Latent Reasoning with Normalizing Flows
  7. 2023Chain-of-Thought Tuning: Masked Language Models can also Think Step By Step in Natural Language Understanding
  8. 2023ThoughtSource: A central hub for large language model reasoning data