Evaluation

MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property COLING 2024 MSLC24: Further Challenges for Metrics on a Wide Landscape of Translation Quality EMNLP 2024 MSLC24 Submissions to the General Machine Translation Task EMNLP 2024 MT-Bench-101: A Fine-Grained Benchmark for Evaluating Large Language Models in Multi-Turn Dialogues ACL 2024 MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models EMNLP 2024 Multi-Dimensional Machine Translation Evaluation: Model Evaluation and Resource for Korean COLING 2024 MultifacetEval: Multifaceted Evaluation to Probe LLMs in Mastering Medical Knowledge IJCAI 2024 MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models NeurIPS 2024 MVP-Bench: Can Large Vision-Language Models Conduct Multi-level Visual Perception Like Humans? EMNLP 2024 “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language Models ACL 2024 NaturalCodeBench: Examining Coding Performance Mismatch on HumanEval and Natural User Queries ACL 2024 Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics NeurIPS 2024 Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuracies ACL 2024 NewTerm: Benchmarking Real-Time New Terms for Large Language Models with Annual Updates NeurIPS 2024 NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition EMNLP 2024 NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes ACL 2024 NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security NeurIPS 2024 On Efficient and Statistical Quality Estimation for Data Annotation ACL 2024 On the Content Bias in Frechet Video Distance CVPR 2024 On the Estimation of Image-matching Uncertainty in Visual Place Recognition CVPR 2024 On the Faithfulness of Vision Transformer Explanations CVPR 2024 On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods AAAI 2024 On the Relationship between Truth and Political Bias in Language Models EMNLP 2024 On the Reliability of Psychological Scales on Large Language Models EMNLP 2024 On the Rigour of Scientific Writing: Criteria, Analysis, and Insights EMNLP 2024