{"total":56,"rows":[{"id":"2311.08298","title":"A Survey of Confidence Estimation and Calibration in Large Language Models","created":"2023-11-14","cited_by_count":256,"area":null},{"id":"2101.08231","title":"Word Alignment by Fine-tuning Embeddings on Parallel Corpora","created":"2021-01-20","cited_by_count":186,"area":null},{"id":"2402.00367","title":"Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration","created":"2024-02-01","cited_by_count":180,"area":null},{"id":"2203.16804","title":"BRIO: Bringing Order to Abstractive Summarization","created":"2022-03-31","cited_by_count":161,"area":null},{"id":"2302.13439","title":"Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models","created":"2023-02-26","cited_by_count":91,"area":null},{"id":"2301.07779","title":"Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection","created":"2023-01-18","cited_by_count":44,"area":null},{"id":"2306.04459","title":"Uncertainty in Natural Language Processing: Sources, Quantification, and Applications","created":"2023-06-05","cited_by_count":44,"area":null},{"id":"2105.14802","title":"On Compositional Generalization of Neural Machine Translation","created":"2021-05-31","cited_by_count":34,"area":null},{"id":"2211.07443","title":"Calibrated Interpretation: Confidence Estimation in Semantic Parsing","created":"2022-11-14","cited_by_count":33,"area":null},{"id":"2104.08676","title":"Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning","created":"2021-04-18","cited_by_count":31,"area":null},{"id":"2203.07559","title":"On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency","created":"2022-03-14","cited_by_count":31,"area":null},{"id":"2102.05486","title":"Towards More Fine-grained and Reliable NLP Performance Prediction","created":"2021-02-10","cited_by_count":26,"area":null},{"id":"2210.15452","title":"Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity","created":"2022-10-20","cited_by_count":25,"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":"2106.00941","title":"Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation","created":"2021-06-02","cited_by_count":17,"area":null},{"id":"2106.13627","title":"Language Models are Good Translators","created":"2021-06-25","cited_by_count":16,"area":null},{"id":"2405.21028","title":"LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language Models","created":"2024-05-31","cited_by_count":15,"area":null},{"id":"2106.06125","title":"Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation","created":"2021-06-11","cited_by_count":14,"area":null},{"id":"2406.15948","title":"Teaching LLMs to Abstain across Languages via Multilingual Feedback","created":"2024-06-22","cited_by_count":14,"area":null},{"id":"2108.13555","title":"Adaptive Label Smoothing To Regularize Large-Scale Graph Training","created":"2021-08-30","cited_by_count":12,"area":null},{"id":"2404.19318","title":"Calibration of Large Language Models on Code Summarization","created":"2024-04-30","cited_by_count":12,"area":null},{"id":"2103.10291","title":"Smoothing and Shrinking the Sparse Seq2Seq Search Space","created":"2021-03-18","cited_by_count":11,"area":null},{"id":"2108.02401","title":"WeChat Neural Machine Translation Systems for WMT21","created":"2021-08-05","cited_by_count":11,"area":null},{"id":"2301.09008","title":"Poor Man's Quality Estimation: Predicting Reference-Based MT Metrics Without the Reference","created":"2023-01-21","cited_by_count":11,"area":null},{"id":"2305.07021","title":"Simple Token-Level Confidence Improves Caption Correctness","created":"2023-05-11","cited_by_count":11,"area":null},{"id":"2107.10427","title":"Confidence-Aware Scheduled Sampling for Neural Machine Translation","created":"2021-07-22","cited_by_count":10,"area":null},{"id":"2105.15087","title":"Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation","created":"2021-05-31","cited_by_count":9,"area":null},{"id":"2203.12210","title":"Integrating Vectorized Lexical Constraints for Neural Machine Translation","created":"2022-03-23","cited_by_count":9,"area":null},{"id":"2403.18286","title":"Few-Shot Recalibration of Language Models","created":"2024-03-27","cited_by_count":9,"area":null},{"id":"2304.14623","title":"Quality-agnostic Image Captioning to Safely Assist People with Vision Impairment","created":"2023-04-28","cited_by_count":8,"area":null},{"id":"2110.06961","title":"Language Modelling via Learning to Rank","created":"2021-10-13","cited_by_count":7,"area":null},{"id":"2211.03041","title":"Calibration Meets Explanation: A Simple and Effective Approach for Model Confidence Estimates","created":"2022-11-06","cited_by_count":7,"area":null},{"id":"2311.03319","title":"DAIL: Data Augmentation for In-Context Learning via Self-Paraphrase","created":"2023-11-06","cited_by_count":6,"area":null},{"id":"2505.23804","title":"Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies","created":"2025-05-27","cited_by_count":5,"area":null},{"id":"2509.24988","title":"Generalized Correctness Models: Learning Calibrated and Model-Agnostic Correctness Predictors from Historical Patterns","created":"2025-09-29","cited_by_count":5,"area":null},{"id":"2109.06253","title":"Multi-Sentence Resampling: A Simple Approach to Alleviate Dataset Length Bias and Beam-Search Degradation","created":"2021-09-13","cited_by_count":4,"area":null},{"id":"2212.04205","title":"DC-MBR: Distributional Cooling for Minimum Bayesian Risk Decoding","created":"2022-12-08","cited_by_count":4,"area":null},{"id":"2212.04262","title":"ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation","created":"2022-12-08","cited_by_count":4,"area":null},{"id":"2402.17527","title":"Predict the Next Word: Humans exhibit uncertainty in this task and language models _____","created":"2024-02-27","cited_by_count":4,"area":null},{"id":"2203.02889","title":"Focus on the Target's Vocabulary: Masked Label Smoothing for Machine Translation","created":"2022-03-06","cited_by_count":3,"area":null},{"id":"2203.09278","title":"Confidence Calibration for Intent Detection via Hyperspherical Space and Rebalanced Accuracy-Uncertainty Loss","created":"2022-03-17","cited_by_count":2,"area":null},{"id":"2203.11413","title":"Learning Confidence for Transformer-based Neural Machine Translation","created":"2022-03-22","cited_by_count":2,"area":null},{"id":"2205.00659","title":"The Implicit Length Bias of Label Smoothing on Beam Search Decoding","created":"2022-05-02","cited_by_count":2,"area":null},{"id":"2211.13865","title":"Competency-Aware Neural Machine Translation: Can Machine Translation Know its Own Translation Quality?","created":"2022-11-25","cited_by_count":2,"area":null},{"id":"2402.01772","title":"Disentangling the Roles of Target-Side Transfer and Regularization in Multilingual Machine Translation","created":"2024-02-01","cited_by_count":2,"area":null},{"id":"2504.19044","title":"Calibrating Translation Decoding with Quality Estimation on LLMs","created":"2025-04-26","cited_by_count":2,"area":null},{"id":"2305.19498","title":"Perception and Semantic Aware Regularization for Sequential Confidence Calibration","created":"2023-05-31","cited_by_count":1,"area":null},{"id":"2311.03672","title":"CBSiMT: Mitigating Hallucination in Simultaneous Machine Translation with Weighted Prefix-to-Prefix Training","created":"2023-11-07","cited_by_count":1,"area":null},{"id":"2409.18645","title":"The Craft of Selective Prediction: Towards Reliable Case Outcome Classification -- An Empirical Study on European Court of Human Rights Cases","created":"2024-09-27","cited_by_count":1,"area":null},{"id":"2606.17234","title":"Speaking in Self-Assessing Tongues: On the Verbalized Confidence of LLMs in Machine Translation","created":"2026-06-15","cited_by_count":1,"area":null},{"id":"2108.03322","title":"Distilling Transformers for Neural Cross-Domain Search","created":"2021-08-06","cited_by_count":0,"area":null},{"id":"2211.04198","title":"Third-Party Aligner for Neural Word Alignments","created":"2022-11-08","cited_by_count":0,"area":null},{"id":"2302.12367","title":"Extracting Victim Counts from Text","created":"2023-02-23","cited_by_count":0,"area":null},{"id":"2304.13883","title":"Neural Keyphrase Generation: Analysis and Evaluation","created":"2023-04-27","cited_by_count":0,"area":null},{"id":"2604.06723","title":"Fine-grained Approaches for Confidence Calibration of LLMs in Automated Code Revision","created":"2026-04-08","cited_by_count":0,"area":null},{"id":"2608.15940","title":"The Null Token Knows: Reducing Message-Free Hallucination in ASR and NMT","created":"2026-08-16","cited_by_count":0,"area":null}],"next_cursor":null}