{"total":120,"rows":[{"id":"2202.03629","title":"Survey of Hallucination in Natural Language Generation","created":"2022-02-08","cited_by_count":2075,"area":null},{"id":"2305.14739","title":"Trusting Your Evidence: Hallucinate Less with Context-aware Decoding","created":"2023-05-24","cited_by_count":327,"area":null},{"id":"2404.10774","title":"MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents","created":"2024-04-16","cited_by_count":257,"area":"rag"},{"id":"2206.04624","title":"Factuality Enhanced Language Models for Open-Ended Text Generation","created":"2022-06-09","cited_by_count":202,"area":null},{"id":"2203.16804","title":"BRIO: Bringing Order to Abstractive Summarization","created":"2022-03-31","cited_by_count":161,"area":null},{"id":"2212.07981","title":"Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation","created":"2022-12-15","cited_by_count":142,"area":null},{"id":"2204.10757","title":"FaithDial: A Faithful Benchmark for Information-Seeking Dialogue","created":"2022-04-22","cited_by_count":109,"area":null},{"id":"2205.12854","title":"Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors","created":"2022-05-25","cited_by_count":104,"area":null},{"id":"2212.09746","title":"Evaluating Human-Language Model Interaction","created":"2022-12-19","cited_by_count":92,"area":null},{"id":"2305.14239","title":"On Learning to Summarize with Large Language Models as References","created":"2023-05-23","cited_by_count":80,"area":null},{"id":"2306.00186","title":"Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback","created":"2023-05-31","cited_by_count":72,"area":null},{"id":"2402.13249","title":"TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization","created":"2024-02-20","cited_by_count":66,"area":null},{"id":"2205.02444","title":"Cross-modal Contrastive Learning for Speech Translation","created":"2022-05-05","cited_by_count":61,"area":null},{"id":"2312.01701","title":"Mitigating Fine-Grained Hallucination by Fine-Tuning Large Vision-Language Models with Caption Rewrites","created":"2023-12-04","cited_by_count":61,"area":"mllm"},{"id":"2406.11289","title":"A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models","created":"2024-06-17","cited_by_count":52,"area":null},{"id":"2404.03602","title":"Evaluating LLMs at Detecting Errors in LLM Responses","created":"2024-04-04","cited_by_count":50,"area":null},{"id":"2205.07830","title":"FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization","created":"2022-05-16","cited_by_count":49,"area":null},{"id":"2510.06265","title":"Large Language Models Hallucination: A Comprehensive Survey","created":"2025-10-05","cited_by_count":49,"area":null},{"id":"2309.09369","title":"Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles","created":"2023-09-17","cited_by_count":45,"area":null},{"id":"2212.10622","title":"mFACE: Multilingual Summarization with Factual Consistency Evaluation","created":"2022-12-20","cited_by_count":42,"area":null},{"id":"2212.10400","title":"Contrastive Learning Reduces Hallucination in Conversations","created":"2022-12-20","cited_by_count":40,"area":null},{"id":"2210.12378","title":"Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling","created":"2022-10-22","cited_by_count":38,"area":null},{"id":"2212.09968","title":"On Improving Summarization Factual Consistency from Natural Language Feedback","created":"2022-12-20","cited_by_count":38,"area":"alignment"},{"id":"2209.03549","title":"Extractive is not Faithful: An Investigation of Broad Unfaithfulness Problems in Extractive Summarization","created":"2022-09-08","cited_by_count":32,"area":null},{"id":"2303.03278","title":"Faithfulness-Aware Decoding Strategies for Abstractive Summarization","created":"2023-03-06","cited_by_count":31,"area":null},{"id":"2310.06827","title":"Teaching Language Models to Hallucinate Less with Synthetic Tasks","created":"2023-10-10","cited_by_count":31,"area":null},{"id":"2204.10290","title":"Learning to Revise References for Faithful Summarization","created":"2022-04-13","cited_by_count":28,"area":null},{"id":"2203.05227","title":"Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods","created":"2022-03-10","cited_by_count":27,"area":null},{"id":"2210.01877","title":"Towards Improving Faithfulness in Abstractive Summarization","created":"2022-10-04","cited_by_count":27,"area":null},{"id":"2305.07982","title":"Zero-shot Faithful Factual Error Correction","created":"2023-05-13","cited_by_count":26,"area":null},{"id":"2304.08653","title":"On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study","created":"2023-04-17","cited_by_count":25,"area":null},{"id":"2204.00203","title":"Graph Enhanced Contrastive Learning for Radiology Findings Summarization","created":"2022-04-01","cited_by_count":24,"area":null},{"id":"2503.15620","title":"Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings","created":"2025-03-19","cited_by_count":24,"area":null},{"id":"2203.10741","title":"HIBRIDS: Attention with Hierarchical Biases for Structure-aware Long Document Summarization","created":"2022-03-21","cited_by_count":23,"area":null},{"id":"2402.17630","title":"Fine-Grained Natural Language Inference Based Faithfulness Evaluation for Diverse Summarisation Tasks","created":"2024-02-27","cited_by_count":23,"area":null},{"id":"2205.08943","title":"CREATER: CTR-driven Advertising Text Generation with Controlled Pre-Training and Contrastive Fine-Tuning","created":"2022-05-18","cited_by_count":17,"area":null},{"id":"2210.06748","title":"Shortcomings of Question Answering Based Factuality Frameworks for Error Localization","created":"2022-10-13","cited_by_count":15,"area":null},{"id":"2303.03948","title":"A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course Summarization","created":"2023-03-07","cited_by_count":14,"area":null},{"id":"2410.07473","title":"Localizing Factual Inconsistencies in Attributable Text Generation","created":"2024-10-09","cited_by_count":14,"area":null},{"id":"2211.03524","title":"Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions","created":"2022-11-07","cited_by_count":13,"area":null},{"id":"2502.11948","title":"HalluEntity: Benchmarking and Understanding Entity-Level Hallucination Detection","created":"2025-02-17","cited_by_count":13,"area":null},{"id":"2208.12306","title":"Multimedia Generative Script Learning for Task Planning","created":"2022-08-25","cited_by_count":12,"area":null},{"id":"2210.11777","title":"Analyzing and Evaluating Faithfulness in Dialogue Summarization","created":"2022-10-21","cited_by_count":12,"area":null},{"id":"2110.07166","title":"CaPE: Contrastive Parameter Ensembling for Reducing Hallucination in Abstractive Summarization","created":"2021-10-14","cited_by_count":11,"area":null},{"id":"2311.09521","title":"AMRFact: Enhancing Summarization Factuality Evaluation with AMR-Driven Negative Samples Generation","created":"2023-11-16","cited_by_count":11,"area":null},{"id":"2411.16638","title":"Do Automatic Factuality Metrics Measure Factuality? A Critical Evaluation","created":"2024-11-25","cited_by_count":11,"area":null},{"id":"2301.10483","title":"SWING: Balancing Coverage and Faithfulness for Dialogue Summarization","created":"2023-01-25","cited_by_count":10,"area":null},{"id":"2305.14069","title":"Evaluating Factual Consistency of Summaries with Large Language Models","created":"2023-05-23","cited_by_count":10,"area":null},{"id":"2305.16548","title":"Annotating and Detecting Fine-grained Factual Errors for Dialogue Summarization","created":"2023-05-26","cited_by_count":10,"area":null},{"id":"2310.13340","title":"Large-Scale and Multi-Perspective Opinion Summarization with Diverse Review Subsets","created":"2023-10-20","cited_by_count":10,"area":null},{"id":"2402.03509","title":"Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains","created":"2024-02-05","cited_by_count":10,"area":null},{"id":"2305.01951","title":"Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization","created":"2023-05-03","cited_by_count":9,"area":null},{"id":"2307.04507","title":"Improving Factuality of Abstractive Summarization via Contrastive Reward Learning","created":"2023-07-10","cited_by_count":9,"area":null},{"id":"2311.02271","title":"FaMeSumm: Investigating and Improving Faithfulness of Medical Summarization","created":"2023-11-03","cited_by_count":9,"area":null},{"id":"2204.04813","title":"Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning","created":"2022-04-11","cited_by_count":8,"area":null},{"id":"2205.12416","title":"Counterfactual Data Augmentation improves Factuality of Abstractive Summarization","created":"2022-05-25","cited_by_count":8,"area":null},{"id":"2205.12467","title":"R2D2: Robust Data-to-Text with Replacement Detection","created":"2022-05-25","cited_by_count":8,"area":null},{"id":"2212.04257","title":"Momentum Calibration for Text Generation","created":"2022-12-08","cited_by_count":8,"area":null},{"id":"2305.03276","title":"Expository Text Generation: Imitate, Retrieve, Paraphrase","created":"2023-05-05","cited_by_count":8,"area":null},{"id":"2305.07615","title":"What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization","created":"2023-05-12","cited_by_count":8,"area":null},{"id":"2305.12289","title":"Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond","created":"2023-05-20","cited_by_count":8,"area":null},{"id":"2305.19339","title":"Less Likely Brainstorming: Using Language Models to Generate Alternative Hypotheses","created":"2023-05-30","cited_by_count":8,"area":null},{"id":"2310.14981","title":"Fidelity-Enriched Contrastive Search: Reconciling the Faithfulness-Diversity Trade-Off in Text Generation","created":"2023-10-23","cited_by_count":8,"area":null},{"id":"2403.06326","title":"From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification","created":"2024-03-10","cited_by_count":8,"area":"alignment"},{"id":"2502.06185","title":"Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document Summarization","created":"2025-02-10","cited_by_count":8,"area":null},{"id":"2203.10133","title":"Probing Factually Grounded Content Transfer with Factual Ablation","created":"2022-03-18","cited_by_count":7,"area":null},{"id":"2305.14981","title":"Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality","created":"2023-05-24","cited_by_count":7,"area":null},{"id":"2310.05857","title":"Improving Summarization with Human Edits","created":"2023-10-09","cited_by_count":7,"area":null},{"id":"2406.16069","title":"FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models","created":"2024-06-23","cited_by_count":7,"area":null},{"id":"2209.13101","title":"WikiDes: A Wikipedia-Based Dataset for Generating Short Descriptions from Paragraphs","created":"2022-09-27","cited_by_count":6,"area":null},{"id":"2305.04782","title":"HistAlign: Improving Context Dependency in Language Generation by Aligning with History","created":"2023-05-08","cited_by_count":6,"area":null},{"id":"2305.14548","title":"Interpretable Automatic Fine-grained Inconsistency Detection in Text Summarization","created":"2023-05-23","cited_by_count":6,"area":null},{"id":"2310.19347","title":"Improving Factual Consistency of News Summarization by Contrastive Preference Optimization","created":"2023-10-30","cited_by_count":6,"area":"alignment"},{"id":"2311.11375","title":"ML-LMCL: Mutual Learning and Large-Margin Contrastive Learning for Improving ASR Robustness in Spoken Language Understanding","created":"2023-11-19","cited_by_count":6,"area":null},{"id":"2406.14709","title":"Factual Dialogue Summarization via Learning from Large Language Models","created":"2024-06-20","cited_by_count":6,"area":null},{"id":"2209.00484","title":"Focus-Driven Contrastive Learniang for Medical Question Summarization","created":"2022-09-01","cited_by_count":5,"area":null},{"id":"2304.07437","title":"Medical Question Summarization with Entity-driven Contrastive Learning","created":"2023-04-15","cited_by_count":5,"area":null},{"id":"2307.00963","title":"Challenges in Domain-Specific Abstractive Summarization and How to Overcome them","created":"2023-07-03","cited_by_count":5,"area":null},{"id":"2402.12821","title":"Identifying Factual Inconsistencies in Summaries: Grounding LLM Inference via Task Taxonomy","created":"2024-02-20","cited_by_count":5,"area":null},{"id":"2409.15090","title":"Using Similarity to Evaluate Factual Consistency in Summaries","created":"2024-09-23","cited_by_count":5,"area":null},{"id":"2502.13674","title":"SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation","created":"2025-02-19","cited_by_count":5,"area":null},{"id":"2202.05943","title":"Semi-supervised New Event Type Induction and Description via Contrastive Loss-Enforced Batch Attention","created":"2022-02-12","cited_by_count":4,"area":null},{"id":"2211.00294","title":"FRSUM: Towards Faithful Abstractive Summarization via Enhancing Factual Robustness","created":"2022-11-01","cited_by_count":4,"area":null},{"id":"2212.05789","title":"Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning","created":"2022-12-12","cited_by_count":4,"area":null},{"id":"2305.19230","title":"Controlled Text Generation with Hidden Representation Transformations","created":"2023-05-30","cited_by_count":4,"area":null},{"id":"2308.06488","title":"Generating Faithful Text From a Knowledge Graph with Noisy Reference Text","created":"2023-08-12","cited_by_count":4,"area":null},{"id":"2310.08764","title":"Calibrating Likelihoods towards Consistency in Summarization Models","created":"2023-10-12","cited_by_count":4,"area":null},{"id":"2310.13499","title":"DistillCSE: Distilled Contrastive Learning for Sentence Embeddings","created":"2023-10-20","cited_by_count":4,"area":"distill"},{"id":"2412.10689","title":"Learning to Verify Summary Facts with Fine-Grained LLM Feedback","created":"2024-12-14","cited_by_count":4,"area":"alignment"},{"id":"2209.00068","title":"Incorporating Task-specific Concept Knowledge into Script Learning","created":"2022-08-31","cited_by_count":3,"area":null},{"id":"2210.12367","title":"Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation","created":"2022-10-22","cited_by_count":3,"area":null},{"id":"2210.13673","title":"Evaluating Parameter Efficient Learning for Generation","created":"2022-10-25","cited_by_count":3,"area":null},{"id":"2210.15553","title":"Improving abstractive summarization with energy-based re-ranking","created":"2022-10-27","cited_by_count":3,"area":null},{"id":"2309.08873","title":"X-PARADE: Cross-Lingual Textual Entailment and Information Divergence across Paragraphs","created":"2023-09-16","cited_by_count":3,"area":null},{"id":"2505.19327","title":"Paying Alignment Tax with Contrastive Learning","created":"2025-05-25","cited_by_count":3,"area":"alignment"},{"id":"2211.08464","title":"ED-FAITH: Evaluating Dialogue Summarization on Faithfulness","created":"2022-11-15","cited_by_count":2,"area":null},{"id":"2305.06647","title":"PROM: A Phrase-level Copying Mechanism with Pre-training for Abstractive Summarization","created":"2023-05-11","cited_by_count":2,"area":null},{"id":"2305.12767","title":"D$^2$TV: Dual Knowledge Distillation and Target-oriented Vision Modeling for Many-to-Many Multimodal Summarization","created":"2023-05-22","cited_by_count":2,"area":"distill"},{"id":"2307.06524","title":"Agreement Tracking for Multi-Issue Negotiation Dialogues","created":"2023-07-13","cited_by_count":2,"area":null},{"id":"2308.15711","title":"Optimizing Factual Accuracy in Text Generation through Dynamic Knowledge Selection","created":"2023-08-30","cited_by_count":2,"area":null}],"next_cursor":"100"}