mlsanityData to 7 Oct 2026

ERA-CoT: Improving Chain-of-Thought through Entity Relationship Analysis

arXiv 2403.06932 ↗First posted 11 Mar 2024cs.CLcited by 18

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

Abstract (arXiv)

Large language models (LLMs) have achieved commendable accomplishments in various natural language processing tasks. However, LLMs still encounter significant challenges when dealing with complex scenarios involving multiple entities. These challenges arise from the presence of implicit relationships that demand multi-step reasoning. In this paper, we propose a novel approach ERA-CoT, which aids LLMs in understanding context by capturing relationships between entities and supports the reasoning of diverse tasks through Chain-of-Thoughts (CoT). Experimental results show that ERA-CoT demonstrates the superior performance of our proposed method compared to current CoT prompting methods, achieving a significant improvement of an average of 5.1% on GPT3.5 compared to previous SOTA baselines. Our analysis indicates that ERA-CoT increases the LLM's understanding of entity relationships, significantly improves the accuracy of question answering, and enhances the reasoning ability of LLMs.

Key facts. Cited by 18 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 16 of its 49 references that are in the map. First posted on arXiv 11 Mar 2024.

Builds on

16 of 49 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future27 Sep

Other references · 15

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  3. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  4. 2022Training Compute-Optimal Large Language Modelscited by 2,927
  5. 2023ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPTcited by 250
  6. 2022Leveraging Large Language Models for Multiple Choice Question Answeringcited by 199
  7. 2023The Capacity for Moral Self-Correction in Large Language Modelscited by 171
  8. 2023GPT-NER: Named Entity Recognition via Large Language Modelscited by 158
  9. 2022Prompting PaLM for Translation: Assessing Strategies and Performancecited by 144
  10. 2022Internet-augmented language models through few-shot prompting for open-domain question answeringcited by 131
  11. 2023GPT-RE: In-context Learning for Relation Extraction using Large Language Modelscited by 62
  12. 2023Adaptive Machine Translation with Large Language Modelscited by 58
3 more
  1. 2022Self-Prompting Large Language Models for Zero-Shot Open-Domain QAcited by 39
  2. 2023Re-Reading Improves Reasoning in Large Language Modelscited by 37
  3. 2023PromptNER: Prompting For Named Entity Recognitioncited by 35

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 6; 2025: 7; 2026: 5.

18 papers.

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  1. 2024HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Modelscited by 273
  2. 2024Tool-Planner: Task Planning with Clusters across Multiple Toolscited by 32
  3. 2025CAM: A Constructivist View of Agentic Memory for LLM-Based Reading Comprehensioncited by 23
  4. 2025CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thoughtcited by 20
  5. 2024Derailer-Rerailer: Adaptive Verification for Efficient and Reliable Language Model Reasoningcited by 9
  6. 2025KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracingcited by 8
  7. 2025LLaVA-RadZ: Can Multimodal Large Language Models Effectively Tackle Zero-shot Radiology Recognition?cited by 6
  8. 2024Improving Arithmetic Reasoning Ability of Large Language Models through Relation Tuples, Verification and Dynamic Feedbackcited by 4
  9. 2025Understanding Before Reasoning: Enhancing Chain-of-Thought with Iterative Summarization Pre-Promptingcited by 4
  10. 2025HGMEM: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modelingcited by 4
  11. 2026FraudShield: Knowledge Graph Empowered Defense for LLMs against Fraud Attackscited by 3
  12. 2026Only Ask What You Don't Know: Grounded Delta Planning for Efficient Multi-step RAGcited by 3
6 more
  1. 2025KisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?cited by 2
  2. 2024CPA-Enhancer: Chain-of-Thought Prompted Adaptive Enhancer for Object Detection under Unknown Degradationscited by 1
  3. 2024DiVA-DocRE: A Discriminative and Voice-Aware Paradigm for Document-Level Relation Extractioncited by 0
  4. 2026RAG without Forgetting: Continual Query-Infused Key Memorycited by 0
  5. 2026RexDrug: Reliable Multi-Drug Combination Extraction through Reasoning-Enhanced LLMscited by 0
  6. 2026Boosting Knowledge-based Visual Question Answering with Structured Context Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning
  2. 2023ThoughtSource: A central hub for large language model reasoning data
  3. 2024Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs
  4. 2023Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering
  5. 2025ECCoT: A Framework for Enhancing Effective Cognition via Chain of Thought in Large Language Model
  6. 2023Chain-of-Thought Tuning: Masked Language Models can also Think Step By Step in Natural Language Understanding
  7. 2023An automatically discovered chain-of-thought prompt generalizes to novel models and datasets
  8. 2025CoT-RAG: Integrating Chain of Thought and Retrieval-Augmented Generation to Enhance Reasoning in Large Language Models