{"total":28,"rows":[{"id":"2306.10193","title":"Conformal Language Modeling","created":"2023-06-16","cited_by_count":170,"area":null},{"id":"2402.10978","title":"Language Models with Conformal Factuality Guarantees","created":"2024-02-15","cited_by_count":131,"area":null},{"id":"2401.12794","title":"Benchmarking LLMs via Uncertainty Quantification","created":"2024-01-23","cited_by_count":126,"area":null},{"id":"2406.02543","title":"To Believe or Not to Believe Your LLM","created":"2024-06-04","cited_by_count":120,"area":null},{"id":"2307.15703","title":"Uncertainty in Natural Language Generation: From Theory to Applications","created":"2023-07-28","cited_by_count":61,"area":null},{"id":"2405.01563","title":"Mitigating LLM Hallucinations via Conformal Abstention","created":"2024-04-04","cited_by_count":59,"area":null},{"id":"2405.01976","title":"Conformal Prediction for Natural Language Processing: A Survey","created":"2024-05-03","cited_by_count":53,"area":null},{"id":"2410.06494","title":"Conformal Prediction: A Data Perspective","created":"2024-10-09","cited_by_count":25,"area":null},{"id":"2501.00555","title":"Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction","created":"2024-12-31","cited_by_count":18,"area":null},{"id":"2309.03797","title":"Conformal Autoregressive Generation: Beam Search with Coverage Guarantees","created":"2023-09-07","cited_by_count":16,"area":null},{"id":"2306.01549","title":"Evaluating Machine Translation Quality with Conformal Predictive Distributions","created":"2023-06-02","cited_by_count":9,"area":null},{"id":"2402.18734","title":"Priority Sampling of Large Language Models for Compilers","created":"2024-02-28","cited_by_count":8,"area":null},{"id":"2306.06221","title":"Conformalizing Machine Translation Evaluation","created":"2023-06-09","cited_by_count":5,"area":null},{"id":"2407.01122","title":"Calibrated Large Language Models for Binary Question Answering","created":"2024-07-01","cited_by_count":3,"area":null},{"id":"2409.19984","title":"CONTESTS: a Framework for Consistency Testing of Span Probabilities in Language Models","created":"2024-09-30","cited_by_count":3,"area":null},{"id":"2510.21310","title":"Efficient semantic uncertainty quantification in language models via diversity-steered sampling","created":"2025-10-24","cited_by_count":2,"area":null},{"id":"2605.08313","title":"Seed Hijacking of LLM Sampling and Quantum Random Number Defense","created":"2026-05-08","cited_by_count":2,"area":null},{"id":"2412.19361","title":"Dynamic Skill Adaptation for Large Language Models","created":"2024-12-26","cited_by_count":1,"area":null},{"id":"2603.05352","title":"Ailed: A Psyche-Driven Chess Engine with Dynamic Emotional Modulation","created":"2026-03-05","cited_by_count":1,"area":null},{"id":"2606.02430","title":"Not All Errors Are Equal: A Systematic Study of Error Propagation in Large Language Model Inference","created":"2026-06-01","cited_by_count":1,"area":null},{"id":"2411.06722","title":"Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models","created":"2024-11-11","cited_by_count":0,"area":null},{"id":"2503.22092","title":"Leveraging LLMs for Predicting Unknown Diagnoses from Clinical Notes","created":"2025-03-28","cited_by_count":0,"area":null},{"id":"2508.05581","title":"Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models","created":"2025-08-07","cited_by_count":0,"area":null},{"id":"2509.04733","title":"CoVeR: Conformal Calibration for Versatile and Reliable Autoregressive Next-Token Prediction","created":"2025-09-05","cited_by_count":0,"area":null},{"id":"2601.19488","title":"Entropy-Guided k-Guard Sampling for Long-Horizon Autoregressive Video Generation","created":"2026-01-27","cited_by_count":0,"area":null},{"id":"2606.28730","title":"Full Conformal Prediction under Stochastic Non-Conformity Measure","created":"2026-06-27","cited_by_count":0,"area":null},{"id":"2609.04445","title":"Conformity Breaks Conformal Prediction","created":"2026-09-03","cited_by_count":0,"area":null},{"id":"2610.15570","title":"Truncation Samplers Are Nested: Comparing Decoding Rules Is a Measurement Problem","created":"2026-10-11","cited_by_count":0,"area":null}],"next_cursor":null}