mlsanityData to 14 Oct 2026

Context-faithful Prompting for Large Language Models

arXiv 2303.11315 ↗First posted 20 Mar 2023cs.CLcited by 80

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Abstract (arXiv)

Large language models (LLMs) encode parametric knowledge about world facts and have shown remarkable performance in knowledge-driven NLP tasks. However, their reliance on parametric knowledge may cause them to overlook contextual cues, leading to incorrect predictions in context-sensitive NLP tasks (e.g., knowledge acquisition tasks). In this paper, we seek to assess and enhance LLMs' contextual faithfulness in two aspects: knowledge conflict and prediction with abstention. We demonstrate that LLMs' faithfulness can be significantly improved using carefully designed prompting strategies. In particular, we identify opinion-based prompts and counterfactual demonstrations as the most effective methods. Opinion-based prompts reframe the context as a narrator's statement and inquire about the narrator's opinions, while counterfactual demonstrations use instances containing false facts to improve faithfulness in knowledge conflict situations. Neither technique requires additional training. We conduct experiments on three datasets of two standard NLP tasks, machine reading comprehension and relation extraction, and the results demonstrate significant improvement in faithfulness to contexts. Code and data are released at https://github.com/wzhouad/context-faithful-llm.

Key facts. Cited by 80 papers in the map (data through 14 Oct 2026). Builds on 48 of its 58 references that are in the map. First posted on arXiv 20 Mar 2023.

Builds on

48 of 58 references.

References · 48

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36 more
  1. 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,955
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  18. 2020Pretrained Transformers Improve Out-of-Distribution Robustnesscited by 294
  19. 2022Prompting GPT-3 To Be Reliablecited by 260
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 18; 2024: 21; 2025: 16; 2026: 25.

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  1. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 698
  2. 2023Making Retrieval-Augmented Language Models Robust to Irrelevant Contextcited by 369
  3. 2023Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflictscited by 341
  4. 2023Trusting Your Evidence: Hallucinate Less with Context-aware Decodingcited by 327
  5. 2023Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificitycited by 206
  6. 2024Know Your Limits: A Survey of Abstention in Large Language Modelscited by 121
  7. 2024AutoSurvey: Large Language Models Can Automatically Write Surveyscited by 119
  8. 2024FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"cited by 86
  9. 2023In-context Pretraining: Language Modeling Beyond Document Boundariescited by 79
  10. 2023Automatic Evaluation of Attribution by Large Language Modelscited by 72
  11. 2024Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Charactercited by 68
  12. 2024Evaluating LLMs at Detecting Errors in LLM Responsescited by 50
38 more
  1. 2023Understanding Retrieval Augmentation for Long-Form Question Answeringcited by 45
  2. 2025Parameters vs. Context: Fine-Grained Control of Knowledge Reliance in Language Modelscited by 39
  3. 2024IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neuronscited by 38
  4. 2023When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Taskscited by 37
  5. 2024Debiasing Multimodal Large Language Models via Penalization of Language Priorscited by 37
  6. 2023How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advancescited by 33
  7. 2023Teaching Language Models to Hallucinate Less with Synthetic Taskscited by 31
  8. 2025Taming Knowledge Conflicts in Language Modelscited by 30
  9. 2024Unraveling Cross-Modality Knowledge Conflicts in Large Vision-Language Modelscited by 28
  10. 2024Cofca: A Step-Wise Counterfactual Multi-hop QA benchmarkcited by 27
  11. 2024Controllable Context Sensitivity and the Knob Behind Itcited by 23
  12. 2024Improving Context-Aware Preference Modeling for Language Modelscited by 22
  13. 2023A Causal View of Entity Bias in (Large) Language Modelscited by 21
  14. 2024Preemptive Answer "Attacks" on Chain-of-Thought Reasoningcited by 19
  15. 2024Long-Form Answers to Visual Questions from Blind and Low Vision Peoplecited by 18
  16. 2023MenatQA: A New Dataset for Testing the Temporal Comprehension and Reasoning Abilities of Large Language Modelscited by 15
  17. 2023Getting Sick After Seeing a Doctor? Diagnosing and Mitigating Knowledge Conflicts in Event Temporal Reasoningcited by 13
  18. 2024Evaluating LLM-based Personal Information Extraction and Countermeasurescited by 12
  19. 2023"Merge Conflicts!" Exploring the Impacts of External Distractors to Parametric Knowledge Graphscited by 11
  20. 2025ParamMute: Suppressing Knowledge-Critical FFNs for Faithful Retrieval-Augmented Generationcited by 11
  21. 2024Context-Parametric Inversion: Why Instruction Finetuning Can Worsen Context Reliancecited by 10
  22. 2023Let Me Teach You: Pedagogical Foundations of Feedback for Language Modelscited by 9
  23. 2025Mitigating Modal Imbalance in Multimodal Reasoningcited by 8
  24. 2023Robustness Over Time: Understanding Adversarial Examples' Effectiveness on Longitudinal Versions of Large Language Modelscited by 7
  25. 2026Investigating Tool-Memory Conflicts in Tool-Augmented LLMscited by 6
  26. 2025ALAS: A Stateful Multi-LLM Agent Framework for Disruption-Aware Planningcited by 5
  27. 2024Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summariescited by 4
  28. 2024Familiarity-Aware Evidence Compression for Retrieval-Augmented Generationcited by 4
  29. 2024Trustworthy Alignment of Retrieval-Augmented Large Language Models via Reinforcement Learningcited by 4
  30. 2025Vibe Check: Understanding the Effects of LLM-Based Conversational Agents' Personality and Alignment on User Perceptions in Goal-Oriented Taskscited by 4
  31. 2025Epidemiology of Large Language Models: A Benchmark for Observational Distribution Knowledgecited by 3
  32. 2025ALAS: Transactional and Dynamic Multi-Agent LLM Planningcited by 3
  33. 2026PromptCD: Test-Time Behavior Enhancement via Polarity-Prompt Contrastive Decodingcited by 3
  34. 2024HINTs: Sensemaking on large collections of documents with Hypergraph visualization and INTelligent agentscited by 2
  35. 2025Investigating Retrieval-Augmented Generation in Quranic Studies: A Study of 13 Open-Source Large Language Modelscited by 2
  36. 2025Know Or Not: a library for evaluating out-of-knowledge base robustnesscited by 2
  37. 2025Copy-Paste to Mitigate Large Language Model Hallucinationscited by 2
  38. 2025COSTAR-A: A prompting framework for enhancing Large Language Model performance on Point-of-View questionscited by 2

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