adv glue
Harbor adapteradv glue — AI evaluation benchmark listed by opencompass.
- Samples
- 121
- Released
- 2021
- Scores
- 0
Directory
6,820 benchmarks indexed, 718 runnable through Harbor. Snapshot generated 2026-10-13. Each card shows a data-quality badge; verified, runnable entries are listed first.
adv glue — AI evaluation benchmark listed by opencompass.
AgentBench: 8环境多任务Agent
A benchmark for grounded agricultural recognition measuring joint identity and localization correctness plus abstention on 1,480 human-verified images.
Adversarial NLI (ANLI) is a dataset collected via an iterative, adversarial human-and-model-in-the-loop procedure.
The focus of language model evaluation has transitioned towards reasoning and knowledge intensive tasks, driven by advancements in pretraining large models.
ARC-AGI-2: 更难的抽象推理
ARC-Eval is a dataset of 7,787 multiple-choice science questions designed to evaluate reasoning capabilities in AI systems.
ASDiv (Academia Sinica Diverse MWP Dataset) is a diverse (in terms of both language patterns and problem types) English math word problem (MWP) corpus for evaluating the capability of various MWP solvers.
In recent years, the input context sizes of large language models (LLMs) have increased dramatically.
BIG-Bench Hard evaluates advanced reasoning capabilities across 23 challenging tasks using over 6,500 English samples.
BBQ: 社会偏见检测
The Beyond the Imitation Game Benchmark (BIG-bench) is a collaborative benchmark intended to probe large language models and extrapolate their future capabilities.
Bongard-OpenWorld is a new benchmark for evaluating real-world few-shot reasoning for machine vision.
Reading comprehension dataset that queries for complex, non-factoid information, and require difficult entailment-like inference to solve.
BrowseComp: 网页搜索研究任务
C-Eval: 中文综合评估
CaseHOLD (Case Holdings On Legal Decisions) is a multiple choice question answering scenario where the task is to identify the relevant holding of a cited case [(Zheng et al, 2021)](https://arxiv.org/pdf/2104.08671.pdf).
ChartQA: 图表理解问答
CodeContests: DeepMind编程竞赛
CommonsenseQA is a multiple-choice question answering dataset that requires different types of commonsense knowledge to predict the correct answers.
DROP is a QA dataset which tests comprehensive understanding of paragraphs.
FrontierScience evaluates AI models on expert-level scientific tasks derived from Olympiad problems and research literature to assess advanced reasoning capabilities.
GAIA: 多步工具使用+推理
GPQA Diamond is a graduate-level multiple-choice benchmark containing 198 questions in biology, physics, and chemistry designed to test models without reliance on search engines.