precision and recall

A Unifying Information-theoretic Perspective on Evaluating Generative Models AAAI 2025 Beyond Pointwise Scores: Decomposed Criteria-Based Evaluation of LLM Responses EMNLP 2025 Formal Quality Measures for Predictors in Markov Decision Processes AAAI 2025 Generate but Verify: Answering with Faithfulness in RAG-based Question Answering IJCNLP 2025 Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling ICML 2024 NovoBench: Benchmarking Deep Learning-based \emph{De Novo} Sequencing Methods in Proteomics NeurIPS 2024 Using ChatGPT for Annotation of Attitude within the Appraisal Theory: Lessons Learned EACL 2024 Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High Dimensions ICML 2023 TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models NeurIPS 2023 WRF: Weighted Rouge-F1 Metric for Entity Recognition AACL 2023 Materialized Knowledge Bases from Commonsense Transformers ACL 2022 Transparent Human Evaluation for Image Captioning NAACL 2022 On Component Interactions in Two-Stage Recommender Systems NeurIPS 2021 Chinese Grammatical Error Detection Based on BERT Model AACL 2020 Reliable Fidelity and Diversity Metrics for Generative Models ICML 2020 Improved Precision and Recall Metric for Assessing Generative Models NeurIPS 2019 Are GANs Created Equal? A Large-Scale Study NeurIPS 2018 Assessing Generative Models via Precision and Recall NeurIPS 2018 Online F-Measure Optimization NeurIPS 2015