mlsanityData to 7 Oct 2026

Citations and Trust in LLM Generated Responses

arXiv 2501.01303 ↗First posted 2 Jan 2025cs.CL cs.AIcited by 17

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Abstract (arXiv)

Question answering systems are rapidly advancing, but their opaque nature may impact user trust. We explored trust through an anti-monitoring framework, where trust is predicted to be correlated with presence of citations and inversely related to checking citations. We tested this hypothesis with a live question-answering experiment that presented text responses generated using a commercial Chatbot along with varying citations (zero, one, or five), both relevant and random, and recorded if participants checked the citations and their self-reported trust in the generated responses. We found a significant increase in trust when citations were present, a result that held true even when the citations were random; we also found a significant decrease in trust when participants checked the citations. These results highlight the importance of citations in enhancing trust in AI-generated content.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Builds on 15 of its 49 references that are in the map. First posted on arXiv 2 Jan 2025.

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15 of 49 references.

References · 15

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  4. 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,841
  5. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,800
  6. 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,201
  7. 2017Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPRcited by 1,086
  8. 2023The Internal State of an LLM Knows When It's Lyingcited by 644
  9. 2019Explaining Machine Learning Classifiers through Diverse Counterfactual Explanationscited by 612
  10. 2023Explainability for Large Language Models: A Surveycited by 331
  11. 2020Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Makingcited by 281
  12. 2018Manipulating and Measuring Model Interpretabilitycited by 256
3 more
  1. 2022Demystifying Prompts in Language Models via Perplexity Estimationcited by 215
  2. 2019Automated Rationale Generation: A Technique for Explainable AI and its Effects on Human Perceptionscited by 81
  3. 2024Reliable, Adaptable, and Attributable Language Models with Retrievalcited by 73

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 9.

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  1. 2025Conformal Linguistic Calibration: Trading-off between Factuality and Specificitycited by 20
  2. 2025Epistemic Alignment: A Mediating Framework for User-LLM Knowledge Deliverycited by 14
  3. 2025SSRL: Self-Search Reinforcement Learningcited by 13
  4. 2025A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomycited by 9
  5. 2026FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAGcited by 6
  6. 2025Transparentize the Internal and External Knowledge Utilization in LLMs with Trustworthy Citationcited by 4
  7. 2025Source Coverage and Citation Bias in LLM-based vs. Traditional Search Enginescited by 4
  8. 2025Towards a Multimodal Document-grounded Conversational AI System for Educationcited by 3
  9. 2025Reallocating Attention Across Layers to Reduce Multimodal Hallucinationcited by 3
  10. 2026When AI Persuades: Adversarial Explanation Attacks on Human Trust in AI-Assisted Decision Makingcited by 2
  11. 2026Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?cited by 1
  12. 2026Aligning Large Language Model Behavior with Human Citation Preferencescited by 1
5 more
  1. 2026Quantifying Uncertainty in AI Visibility: A Statistical Framework for Generative Search Measurementcited by 1
  2. 2026SourceBench: Can AI Answers Reference Quality Web Sources?cited by 0
  3. 2026VetScore: Risk-Weighted Fact Verification for Veterinary Long-Form QA with Citationscited by 0
  4. 2026Data Citation for Large Language Models: A Challengecited by 0
  5. 2026WildSEEK: Evaluating Language Models for Information-Seekingcited by 0