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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

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01neko-llm /eval-Qwen3-32B-HLEtext1K<n<10K0 likes1.9k downloads1y agoHugging Face02dvcorg /test-datachain-llm-evaltextn<1K1 likes1.2k downloads3h agoHugging Face03neko-llm /eval-result-Qwen3-32B-HLE neko-llm/eval-result-Qwen3-32B-HLE Judged HLE evaluation results uploaded via script. Summary metrics Total examples: 2129 Accuracy: 7.4213% ± 1.1134% Average confidence: 93.9% Calibration error (L2): 83.6859% Models neko-llm/Qwen3-32B-HLE Columns id model response usage (JSON string) judge_correct_answer judge_model_answer judge_reasoning judge_correct judge_confidence judge_response (raw JSON) Generated by evaluation/hle/upload_eval_result.py text1K<n<10K0 likes308 downloads1y agoHugging Face04MultiverseComputingCAI /llm-refusal-evaluation 🛡️ LLM Refusal Evaluation Benchmark This repository contains the benchmarks used in the LLM-Refusal-Evaluation suite. The prompts are organized into three groups: Safety Benchmarks — harmful / jailbreak-style prompts that models should refuse. Chinese Sensitive Topics — prompts that may be censored by China-aligned models. Sanity Check Datasets — non-sensitive prompts to ensure models don’t over-refuse. 📌 Contents Safety Benchmarks JailbreakBench SorryBench… See the full description on the dataset page: https://huggingface.co/datasets/MultiverseComputingCAI/llm-refusal-evaluation.texttext-generation1K<n<10K5 likes240 downloads9mo agoHugging Face05jang1563 /llm-sfm-safety-eval LLM x SFM Safety Evaluation When a general-purpose language model interprets the output of a specialist science foundation model (a protein, genomic, RNA, or chemistry model), does its safety behavior recognize the scientific content, or only the surface form of the request? This repository is the empirical core of a study of that question: the evaluation harness, the redacted aggregate results, and the measurement specifications behind four findings about how deployed Claude… See the full description on the dataset page: https://huggingface.co/datasets/jang1563/llm-sfm-safety-eval.texttext-classification10K<n<100K0 likes207 downloads15d agoHugging Face06cjvt /slovenian-llm-eval Slovenian LLM Evaluation Dataset This dataset is designed for evaluating Slovenian language models and builds upon the work of gordicaleksa/slovenian-llm-eval-v0 which translated some of the popular English benchmarks into Slovenian by using Google Translate. We have further improved the quality of the Slovenian translations. The dataset contains the following benchmarks: ARC Challenge ARC Easy BoolQ GSM8K HellaSwag NQ Open OpenBookQA PIQA TriviaQA TruthfulQA Winogrande… See the full description on the dataset page: https://huggingface.co/datasets/cjvt/slovenian-llm-eval.tabular100K<n<1M0 likes179 downloads5mo agoHugging Face07zenless-lab /llm-jp-evaltext100K<n<1M0 likes155 downloads2y agoHugging Face08mteb /llm-eval-massive_intenttext10K<n<100K0 likes154 downloads6mo agoHugging Face09orionweller /llm-based-expansions-eval-datasetstext10M<n<100M0 likes143 downloads2y agoHugging Face10mteb /llm-eval-massive_scenariotext10K<n<100K0 likes135 downloads6mo agoHugging Face11k-mktr /llm_eval_promptstextquestion-answering1K<n<10K1 likes132 downloads2y agoHugging Face12mteb /llm-eval-imdbtext10K<n<100K0 likes126 downloads7mo agoHugging Face13mteb /llm-eval-mtop_domaintext10K<n<100K0 likes125 downloads6mo agoHugging Face14mteb /llm-eval-banking77text10K<n<100K0 likes122 downloads7mo agoHugging Face15MinaGabriel /llm-fol-reasoning-eval LLM FOL Reasoning Eval This dataset is derived from ProverQA, a First-Order Logic reasoning benchmark designed to test the ability of large language models (LLMs) to perform structured logical reasoning.It restructures and normalizes the ProverQA development and training data into a unified, clean format suitable for evaluating chain-of-thought (CoT) and symbolic reasoning capabilities in LLMs. Source Original dataset: ProverQA: A First-Order Logic Reasoning… See the full description on the dataset page: https://huggingface.co/datasets/MinaGabriel/llm-fol-reasoning-eval.tabulartext-classification1K<n<10K3 likes120 downloads1y agoHugging Face16mteb /llm-eval-amazon_counterfactualtext10K<n<100K0 likes114 downloads6mo agoHugging Face17mteb /llm-eval-amazon_reviewstext1M<n<10M0 likes108 downloads7mo agoHugging Face18mteb /llm-eval-tweet_sentimenttext10K<n<100K0 likes108 downloads6mo agoHugging Face19mteb /llm-eval-toxic_conversationstext10K<n<100K0 likes107 downloads6mo agoHugging Face20neko-llm /eval-Qwen-Qwen3-235B-A22B-openroutertextn<1K0 likes100 downloads1y agoHugging Face21llmeval-fdu /LLMEval-Fair LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models LLMEval-Fair is a 30-month longitudinal study on the robustness and fairness of LLM evaluation, built on a proprietary bank of 220,000+ graduate-level Chinese questions spanning 13 academic disciplines. This is the publicly released subset of that bank. Paper (arXiv): https://arxiv.org/abs/2508.05452 Venue: ACL 2026 Main Conference Project website: https://llmeval.com/ GitHub:… See the full description on the dataset page: https://huggingface.co/datasets/llmeval-fdu/LLMEval-Fair.textquestion-answering100K<n<1M0 likes98 downloads5mo agoHugging Face22BushNate /llm-refusal-evaluation 🛡️ LLM Refusal Evaluation Benchmark This repository contains the benchmarks used in the LLM-Refusal-Evaluation suite. The prompts are organized into three groups: Safety Benchmarks — harmful / jailbreak-style prompts that models should refuse. Chinese Sensitive Topics — prompts that may be censored by China-aligned models. Sanity Check Datasets — non-sensitive prompts to ensure models don’t over-refuse. 📌 Contents Safety Benchmarks JailbreakBench SorryBench… See the full description on the dataset page: https://huggingface.co/datasets/BushNate/llm-refusal-evaluation.texttext-generation1K<n<10K1 likes88 downloads2mo agoHugging Face23MarkrAI /AutoRAG-evaluation-2024-LLM-paper-v1 AutoRAG evaluation dataset Made with 2024 LLM resesarch articles (papers) This dataset is an example for AutoRAG. You can directly use this dataset for optimizng and benchmarking your RAG setup in AutoRAG. How this dataset created? This dataset is 100% synthetically generated by GPT-4 and Marker Inc. technology. At first, we collected 110 latest LLM papers at arxiv. We used Marker OCR model to extract texts. And chunk it using MarkdownSplitter and… See the full description on the dataset page: https://huggingface.co/datasets/MarkrAI/AutoRAG-evaluation-2024-LLM-paper-v1.text1K<n<10K9 likes86 downloads3y agoHugging Face24nlpllmeval /NLP-Course-LLM-Reasoning-Eval-May2025 Overview of LLM Reasoning Eval Dataset This dataset contains evaluation of multiple large language models (LLMs) over 918 MCQ reasoning questions created by 184 students. Each question was used to test 3 LLMs (each 3 times): GPT-4o, Claude Sonnet 3.x (3.5 or 3.7), and Deepseek R1. The questions target various reasoning areas (i.e., Math, Logic, Temporal, Commonsense) and are included only if 3 seperate attempts (in a new session) by ChatGPT (GPT-4o) fail at giving the correct… See the full description on the dataset page: https://huggingface.co/datasets/nlpllmeval/NLP-Course-LLM-Reasoning-Eval-May2025.textn<1K10 likes83 downloads1y agoHugging Face25llmeval-fdu /LLMEval-1 LLMEval-1: Large-Scale Chinese LLM Evaluation (Phase I) LLMEval-1 is the Phase I evaluation dataset of the LLMEval project (Fudan NLP Lab), released alongside the paper "LLMEval: A Preliminary Study on How to Evaluate Large Language Models" (AAAI 2024). It is a Chinese, generative-QA benchmark designed to study how large language models should be evaluated. Paper: https://arxiv.org/abs/2312.07398 Project website: https://llmeval.com/ GitHub: https://github.com/llmeval/LLMEval-1… See the full description on the dataset page: https://huggingface.co/datasets/llmeval-fdu/LLMEval-1.textquestion-answering1K<n<10K0 likes80 downloads5mo agoHugging Face26permitt /serbian-llm-eval Serbian LLM Eval This dataset is a republish of gordicaleksa/serbian-llm-eval-v1 as plain Parquet configs, so it can be loaded with modern versions of the datasets library (the upstream repo ships a Python loading script that datasets can no longer execute). Row contents are otherwise unchanged; only the example_id field is synthesized where the upstream data has no unique identifier, and the triviaqa answer struct is flattened into answer_value / answer_aliases columns.… See the full description on the dataset page: https://huggingface.co/datasets/permitt/serbian-llm-eval.text100K<n<1M0 likes80 downloads2mo agoHugging Face27mteb /llm-eval-public-health-qatextn<1K0 likes79 downloads4mo agoHugging Face28llmeval-fdu /LLMEval-2 LLMEval-2: Professional Domain Evaluation of Chinese LLMs (Phase II) LLMEval-2 is the Phase II evaluation dataset of the LLMEval project (Fudan NLP Lab), released alongside the AAAI 2024 paper "LLMEval: A Preliminary Study on How to Evaluate Large Language Models". While LLMEval-1 focuses on general capabilities, LLMEval-2 targets professional domain evaluation across 12 academic disciplines. Paper: https://arxiv.org/abs/2312.07398 Project website: https://llmeval.com/ GitHub:… See the full description on the dataset page: https://huggingface.co/datasets/llmeval-fdu/LLMEval-2.textquestion-answering1K<n<10K0 likes77 downloads5mo agoHugging Face29nbvbharath-1729 /llm-math-evaluation-dataset LLM Math Response Evaluation Dataset Dataset Summary A human-annotated dataset of 150 AI-generated math responses evaluated across GPT-4o, Claude, and Gemini. Each response is scored on Correctness, Reasoning, and Clarity using a structured rubric, with written justification for every score. Supported Tasks LLM evaluation and benchmarking Math reasoning quality assessment Error type classification in AI responses Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/nbvbharath-1729/llm-math-evaluation-dataset.tabularn<1K0 likes71 downloads5d agoHugging Face30mteb /llm-eval-aila-statutestextn<1K0 likes70 downloads6mo agoHugging Face

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