ContextCite: Attributing Model Generation to Context
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Abstract (arXiv)
How do language models use information provided as context when generating a response? Can we infer whether a particular generated statement is actually grounded in the context, a misinterpretation, or fabricated? To help answer these questions, we introduce the problem of context attribution: pinpointing the parts of the context (if any) that led a model to generate a particular statement. We then present ContextCite, a simple and scalable method for context attribution that can be applied on top of any existing language model. Finally, we showcase the utility of ContextCite through three applications: (1) helping verify generated statements (2) improving response quality by pruning the context and (3) detecting poisoning attacks. We provide code for ContextCite at https://github.com/MadryLab/context-cite.
Key facts. Cited by 93 papers in the map (data through 7 Oct 2026). Builds on 56 of its 74 references that are in the map. First posted on arXiv 1 Sep 2024.
Builds on
56 of 74 references.
References · 56
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- 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,259
- 2022LaMDA: Language Models for Dialog Applicationscited by 1,218
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- 2019Attention is not Explanationcited by 916
- 2019DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphscited by 883
- 2016Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyondcited by 809
- 2022Ignore Previous Prompt: Attack Techniques For Language Modelscited by 760
- 2020Quantifying Attention Flow in Transformerscited by 759
- 2019Universal Adversarial Triggers for Attacking and Analyzing NLPcited by 709
- 2023Enabling Large Language Models to Generate Text with Citationscited by 584
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- 2019Is Attention Interpretable?cited by 387
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- 2016Not Just a Black Box: Learning Important Features Through Propagating Activation Differencescited by 295
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- 2023FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarioscited by 247
- 2020Explaining by Removing: A Unified Framework for Model Explanationcited by 218
- 2015Visualizing and Understanding Neural Models in NLPcited by 199
- 2022Datamodels: Predicting Predictions from Training Datacited by 186
- 2023DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Modelscited by 121
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- 2024Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attackscited by 78
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- 2023PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptionscited by 53
- 2023Sequential Integrated Gradients: a simple but effective method for explaining language modelscited by 52
- 2023Effective Large Language Model Adaptation for Improved Grounding and Citation Generationcited by 44
50 most cited of 56 All 56 (JSON)
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Citing papers per year: 2024: 8; 2025: 46; 2026: 39.
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- 2025Design Patterns for Securing LLM Agents against Prompt Injectionscited by 67
- 2024Steering Away from Harm: An Adaptive Approach to Defending Vision Language Model Against Jailbreakscited by 44
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- 2025TracLLM: A Generic Framework for Attributing Long Context LLMscited by 11
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- 2025Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAGcited by 7
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- 2026Decoupling Token Roles in Autoregressive Pretraining27 Sep 2026
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- 2026The Laws of Context Allocation: Causal Measurement and Closed-Loop Orchestration in Generative Search24 Aug 2026
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- 2026Nonlinear Axiomatic Attribution for Cooperative Games10 Jul 2026
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- 2025MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution5 Dec 2025
- 2025HealthContradict: Evaluating Biomedical Knowledge Conflicts in Language Models2 Dec 2025
- 2025What Really Counts? Examining Step and Token Level Attribution in Multilingual CoT Reasoning19 Nov 2025
- 2025Rule-Based Explanations for Retrieval-Augmented LLM Systems26 Oct 2025
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50 newest of 93 All 93 (JSON)
- 2025Attributing Response to Context: A Jensen-Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generationcited by 12
- 2025Who Taught the Lie? Responsibility Attribution for Poisoned Knowledge in Retrieval-Augmented Generationcited by 12
- 2025Resisting Contextual Interference in RAG via Parametric-Knowledge Reinforcementcited by 11
- 2025Source Attribution in Retrieval-Augmented Generationcited by 7
- 2025Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAGcited by 7
- 2025AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruptioncited by 5
- 2025Transparentize the Internal and External Knowledge Utilization in LLMs with Trustworthy Citationcited by 4
- 2025Context Attribution with Multi-Armed Bandit Optimizationcited by 2
- 2026RUBEN: Rule-Based Explanations for Retrieval-Augmented LLM Systemscited by 1
- 2026ProvenAI: Provenance-Native Traces of Evidence in Generated Answerscited by 1
- 2026Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)cited by 1
- 2025heiDS at ArchEHR-QA 2025: From Fixed-k to Query-dependent-k for Retrieval Augmented Generationcited by 0
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- 2026Feedback-Assisted Trust Propagation over Document Relation Graphs for Retrieval-Augmented Generation1 Sep 2026
- 2026Retrieved But Not Reliable: A Survey on Attacks, and Defenses in Retrieval-Augmented Generation25 Aug 2026
- 2026The Laws of Context Allocation: Causal Measurement and Closed-Loop Orchestration in Generative Search24 Aug 2026
- 2026Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)5 Jul 2026
- 2026ProvenAI: Provenance-Native Traces of Evidence in Generated Answers24 Jun 2026
- 2026How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation9 Jun 2026
- 2026RUBEN: Rule-Based Explanations for Retrieval-Augmented LLM Systems11 May 2026
- 2026Quantifying Retriever-Generator Alignment in RAG with Local Explanations29 Jan 2026
- 2025Rule-Based Explanations for Retrieval-Augmented LLM Systems26 Oct 2025
- 2025Citation Failure: Definition, Analysis and Efficient Mitigation23 Oct 2025
- 2025Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG17 Sep 2025
- 2025Who Taught the Lie? Responsibility Attribution for Poisoned Knowledge in Retrieval-Augmented Generation17 Sep 2025
12 newest of 19 All 19 (JSON)
- 2025Design Patterns for Securing LLM Agents against Prompt Injectionscited by 67
- 2026CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attributioncited by 13
- 2026The Why Behind the Action: Unveiling Internal Drivers via Agentic Attributioncited by 8
- 2026AttriMem: Attribution-Guided Process Feedback for Agent Memory Constructioncited by 3
- 2025Multimedia and Visual Analytics in the Agentic Eracited by 1
- 2026What Guides the Agent? Adjudicating Unauthorized Behavior via Localizing Behavior-Guiding Instructionscited by 1
- 2026Cost-Utility Alignment in LLM Agent Trajectories:Profiling,Attribution,Diagnosis,Adaptation,and Evaluationcited by 1
- 2026Tokengeist: Multi-Turn Attribution Tracing in Agentic Conversationscited by 0
- 2026What Eviction Destroys: A Restore-Counterfactual Audit of Forgetting in Agent Memorycited by 0
- 2026Auditing Agent Actions through Query-Conditioned Attributioncited by 0
- 2026Auditing Agent Actions through Query-Conditioned Attribution27 Sep 2026
- 2026What Eviction Destroys: A Restore-Counterfactual Audit of Forgetting in Agent Memory8 Sep 2026
- 2026Cost-Utility Alignment in LLM Agent Trajectories:Profiling,Attribution,Diagnosis,Adaptation,and Evaluation25 Aug 2026
- 2026What Guides the Agent? Adjudicating Unauthorized Behavior via Localizing Behavior-Guiding Instructions25 Aug 2026
- 2026AttriMem: Attribution-Guided Process Feedback for Agent Memory Construction23 Jul 2026
- 2026Tokengeist: Multi-Turn Attribution Tracing in Agentic Conversations14 Jun 2026
- 2026CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution8 Feb 2026
- 2026The Why Behind the Action: Unveiling Internal Drivers via Agentic Attribution21 Jan 2026
- 2025Design Patterns for Securing LLM Agents against Prompt Injections10 Jun 2025
- 2025Multimedia and Visual Analytics in the Agentic Era8 Apr 2025
- 2026Spurious Rewards Paradox: Mechanistically Understanding How RLVR Activates Memorization Shortcuts in LLMscited by 13
- 2025HoT: Highlighted Chain of Thought for Referencing Supporting Facts from Inputscited by 9
- 2025Explaining the Reasoning of Large Language Models Using Attribution Graphscited by 3
- 2025What Really Counts? Examining Step and Token Level Attribution in Multilingual CoT Reasoningcited by 1
- 2026CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimizationcited by 0
- 2026CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization28 Jul 2026
- 2026Spurious Rewards Paradox: Mechanistically Understanding How RLVR Activates Memorization Shortcuts in LLMs16 Jan 2026
- 2025Explaining the Reasoning of Large Language Models Using Attribution Graphs17 Dec 2025
- 2025What Really Counts? Examining Step and Token Level Attribution in Multilingual CoT Reasoning19 Nov 2025
- 2025HoT: Highlighted Chain of Thought for Referencing Supporting Facts from Inputs3 Mar 2025
- 2024AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attributioncited by 23
- 2024Permissive Information-Flow Analysis for Large Language Modelscited by 22
- 2025ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMscited by 16
- 2025TokenShapley: Token Level Context Attribution with Shapley Valuecited by 14
- 2025LAQuer: Localized Attribution Queries in Content-grounded Generationcited by 13
- 2024LitLLMs, LLMs for Literature Review: Are we there yet?cited by 12
- 2025SPEX: Scaling Feature Interaction Explanations for LLMscited by 12
- 2025Learning to Attribute with Attentioncited by 11
- 2025The Atlas of In-Context Learning: How Attention Heads Shape In-Context Retrieval Augmentationcited by 11
- 2025TracLLM: A Generic Framework for Attributing Long Context LLMscited by 11
- 2025Can LLMs Explain Themselves Counterfactually?cited by 10
- 2025The Role of Sparsity for Length Generalization in Transformerscited by 8
12 most cited of 50 All 50 (JSON)
- 2026Causal Memory Policy: Making Memory Utility Identifiable by Intervening on Retrieval1 Oct 2026
- 2026Is This Evidence Decision-Critical? Learning to Verify Rule-Governed Decisions30 Sep 2026
- 2026Beyond the Shadows of Plato's Cave: Evaluating False Memory in Autonomous Agents via Counterfactual Reasoning30 Sep 2026
- 2026Self-Evolving Agents via Likelihood-Guided Tool-Space Optimization28 Sep 2026
- 2026Decoupling Token Roles in Autoregressive Pretraining27 Sep 2026
- 2026Does a model's stated reason for rejecting a candidate do any work?24 Sep 2026
- 2026DocAttriBench: Benchmarking Answer Grounding in Document Visual Question Answering17 Sep 2026
- 2026When the Wrong Key Wins: Understanding and Detecting Hallucinations in LLMs14 Sep 2026
- 2026Key Path Identification for Resolving Knowledge Conflicts via SAE-based Steering8 Sep 2026
- 2026Fair on the Surface? Benchmarking Hidden-Output Fairness Gaps in LLM Recommenders8 Aug 2026
- 2026How Context Attribution Handles What the Model Already Knows26 Jul 2026
- 2026Nonlinear Axiomatic Attribution for Cooperative Games10 Jul 2026
12 newest of 50 All 50 (JSON)