Correctness is not Faithfulness in RAG Attributions
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Abstract (arXiv)
Retrieving relevant context is a common approach to reduce hallucinations and enhance answer reliability. Explicitly citing source documents allows users to verify generated responses and increases trust. Prior work largely evaluates citation correctness - whether cited documents support the corresponding statements. But citation correctness alone is insufficient. To establish trust in attributed answers, we must examine both citation correctness and citation faithfulness. In this work, we first disentangle the notions of citation correctness and faithfulness, which have been applied inconsistently in previous studies. Faithfulness ensures that the model's reliance on cited documents is genuine, reflecting actual reference use rather than superficial alignment with prior beliefs, which we call post-rationalization. We design an experiment that reveals the prevalent issue of post-rationalization, which undermines reliable attribution and may result in misplaced trust. Our findings suggest that current attributed answers often lack citation faithfulness (up to 57 percent of the citations), highlighting the need to evaluate correctness and faithfulness for trustworthy attribution in language models.
Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 26 of its 59 references that are in the map. First posted on arXiv 23 Dec 2024.
Builds on
26 of 59 references.
References · 26
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
- 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,800
- 2022LaMDA: Language Models for Dialog Applicationscited by 1,218
- 2023Measuring Faithfulness in Chain-of-Thought Reasoningcited by 668
- 2018e-SNLI: Natural Language Inference with Natural Language Explanationscited by 468
- 2022Teaching language models to support answers with verified quotescited by 290
- 2024Knowledge Conflicts for LLMs: A Surveycited by 274
- 2024A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Modelscited by 266
- 2021Measuring Attribution in Natural Language Generation Modelscited by 253
- 2020Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AIcited by 166
14 more
- 2022Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Modelscited by 108
- 2024Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Modelscited by 104
- 2023Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanationscited by 85
- 2023A Survey of Large Language Models Attributioncited by 71
- 2023HAGRID: A Human-LLM Collaborative Dataset for Generative Information-Seeking with Attributioncited by 55
- 2024Attribute First, then Generate: Locally-attributable Grounded Text Generationcited by 54
- 2023PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptionscited by 53
- 2023Resolving Knowledge Conflicts in Large Language Modelscited by 49
- 2019Can I Trust the Explainer? Verifying Post-hoc Explanatory Methodscited by 37
- 2023Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AIcited by 33
- 2024Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generationcited by 25
- 2024Evaluation of RAG Metrics for Question Answering in the Telecom Domaincited by 19
- 2024Towards Fine-Grained Citation Evaluation in Generated Text: A Comparative Analysis of Faithfulness Metricscited by 17
- 2020Robust Conversational AI with Grounded Text Generationcited by 9
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Citing papers per year: 2025: 3; 2026: 15.
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- 2025Deep Research: A Survey of Autonomous Research Agentscited by 63
- 2026EvidenceRL: Reinforcing Evidence Consistency for Trustworthy Language Modelscited by 4
- 2026Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agentscited by 3
- 2026LEDGERMIND: Provenance-Constrained Multimodal Agentic Reasoning with a Structured Evidence Ledgercited by 3
- 2026CUE-R: Beyond the Final Answer in Retrieval-Augmented Generationcited by 2
- 2026Advancing ESG Intelligence: An Expert-level Agent and Comprehensive Benchmark for Sustainable Financecited by 1
- 2026H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversationscited by 1
- 2026Compute Globally, Materialize Locally: The Memory Contract of Sparse Event-KVcited by 1
- 2025Tracing Facts or just Copies? A critical investigation of the Competitions of Mechanisms in Large Language Modelscited by 0
- 2025Jointly Generating and Attributing Answers using Logits of Document-Identifier Tokenscited by 0
- 2026RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasonerscited by 0
- 2026Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAGcited by 0
6 more
- 2026Re-Ranking Through an Attribution Lens for Citation Quality in Legal QAcited by 0
- 2026Per-Entity Bias Mapping for AI Visibility: Why Brand Mentions Require Entity-Specific Calibrationcited by 0
- 2026Evaluating and Guarding Citation Faithfulness in Agentic Scientific Synthesiscited by 0
- 2026VetScore: Risk-Weighted Fact Verification for Veterinary Long-Form QA with Citationscited by 0
- 2026Do LLMs Understand Context? A Knowledge Graph-Based Evaluation Frameworkcited by 0
- 2026Vestrum: Improving Agent Harnesses by Adapting Their Verification, Structure and Memorycited by 0
- 2026Vestrum: Improving Agent Harnesses by Adapting Their Verification, Structure and Memory27 Sep 2026
- 2026Do LLMs Understand Context? A Knowledge Graph-Based Evaluation Framework24 Sep 2026
- 2026VetScore: Risk-Weighted Fact Verification for Veterinary Long-Form QA with Citations4 Aug 2026
- 2026LEDGERMIND: Provenance-Constrained Multimodal Agentic Reasoning with a Structured Evidence Ledger30 Jul 2026
- 2026Compute Globally, Materialize Locally: The Memory Contract of Sparse Event-KV26 Jul 2026
- 2026Evaluating and Guarding Citation Faithfulness in Agentic Scientific Synthesis10 Jul 2026
- 2026Per-Entity Bias Mapping for AI Visibility: Why Brand Mentions Require Entity-Specific Calibration19 Jun 2026
- 2026Re-Ranking Through an Attribution Lens for Citation Quality in Legal QA2 Jun 2026
- 2026Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAG14 May 2026
- 2026H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversations1 May 2026
- 2026RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners30 Apr 2026
- 2026CUE-R: Beyond the Final Answer in Retrieval-Augmented Generation7 Apr 2026
6 more
- 2026Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agents3 Apr 2026
- 2026EvidenceRL: Reinforcing Evidence Consistency for Trustworthy Language Models20 Mar 2026
- 2026Advancing ESG Intelligence: An Expert-level Agent and Comprehensive Benchmark for Sustainable Finance13 Jan 2026
- 2025Deep Research: A Survey of Autonomous Research Agents18 Aug 2025
- 2025Jointly Generating and Attributing Answers using Logits of Document-Identifier Tokens12 Aug 2025
- 2025Tracing Facts or just Copies? A critical investigation of the Competitions of Mechanisms in Large Language Models16 Jul 2025
- 2025Deep Research: A Survey of Autonomous Research Agentscited by 63
- 2026Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agentscited by 3
- 2026Advancing ESG Intelligence: An Expert-level Agent and Comprehensive Benchmark for Sustainable Financecited by 1
- 2026Evaluating and Guarding Citation Faithfulness in Agentic Scientific Synthesiscited by 0
- 2026Vestrum: Improving Agent Harnesses by Adapting Their Verification, Structure and Memorycited by 0
- 2026Vestrum: Improving Agent Harnesses by Adapting Their Verification, Structure and Memory27 Sep 2026
- 2026Evaluating and Guarding Citation Faithfulness in Agentic Scientific Synthesis10 Jul 2026
- 2026Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agents3 Apr 2026
- 2026Advancing ESG Intelligence: An Expert-level Agent and Comprehensive Benchmark for Sustainable Finance13 Jan 2026
- 2025Deep Research: A Survey of Autonomous Research Agents18 Aug 2025
- 2026CUE-R: Beyond the Final Answer in Retrieval-Augmented Generationcited by 2
- 2026H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversationscited by 1
- 2026Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAGcited by 0
- 2026Re-Ranking Through an Attribution Lens for Citation Quality in Legal QAcited by 0
- 2026Re-Ranking Through an Attribution Lens for Citation Quality in Legal QA2 Jun 2026
- 2026Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAG14 May 2026
- 2026H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversations1 May 2026
- 2026CUE-R: Beyond the Final Answer in Retrieval-Augmented Generation7 Apr 2026
- 2026EvidenceRL: Reinforcing Evidence Consistency for Trustworthy Language Modelscited by 4
- 2025Tracing Facts or just Copies? A critical investigation of the Competitions of Mechanisms in Large Language Modelscited by 0
- 2025Jointly Generating and Attributing Answers using Logits of Document-Identifier Tokenscited by 0
- 2026Per-Entity Bias Mapping for AI Visibility: Why Brand Mentions Require Entity-Specific Calibrationcited by 0
- 2026VetScore: Risk-Weighted Fact Verification for Veterinary Long-Form QA with Citationscited by 0
- 2026Do LLMs Understand Context? A Knowledge Graph-Based Evaluation Frameworkcited by 0
- 2026Do LLMs Understand Context? A Knowledge Graph-Based Evaluation Framework24 Sep 2026
- 2026VetScore: Risk-Weighted Fact Verification for Veterinary Long-Form QA with Citations4 Aug 2026
- 2026Per-Entity Bias Mapping for AI Visibility: Why Brand Mentions Require Entity-Specific Calibration19 Jun 2026
- 2026EvidenceRL: Reinforcing Evidence Consistency for Trustworthy Language Models20 Mar 2026
- 2025Jointly Generating and Attributing Answers using Logits of Document-Identifier Tokens12 Aug 2025
- 2025Tracing Facts or just Copies? A critical investigation of the Competitions of Mechanisms in Large Language Models16 Jul 2025
Similar, not cited
Close in wording, no citation either way
- 2024A Comparative Analysis of Faithfulness Metrics and Humans in Citation Evaluation
- 2026How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation
- 2024Attribute or Abstain: Large Language Models as Long Document Assistants
- 2026Attributable Post-Rationalization in RAG Citations: A Controlled Reproduction and an RLVR Comparison
- 2025Generation-Time vs. Post-hoc Citation: A Holistic Evaluation of LLM Attribution
- 2024Abstention vs. Hallucination: Benchmarking LLM Source Attribution for Scientific Citations
- 2026Universal Pathologies, Conditional Consequences: A Triple-Robustness Analysis of RAG for Multi-Hop Traceability
- 2025VeriCite: Towards Reliable Citations in Retrieval-Augmented Generation via Rigorous Verification