arXiv 2610.31494 · cs.CV · 2026-10-22
AgentVQA: A Unified Benchmark for Agentic Visual Understanding
Advait Gupta, Sachin Konan, Tom Yin, Gabriel Sarch, Zhuang Liu
zlab-princeton
在最新榜 #307 本站收录于 2026-10-26
一句话要点
AgentVQA 是离线评测基准，从 23 个数据集人工挑出 1000 个真实智能体示例，覆盖网页智能体、机器人、第一人称视频、游戏和空间规划五类场景，用来评估视觉语言模型的智能体能力。
AgentVQA is an offline benchmark of 1,000 hand-picked real agent examples from 23 datasets across web agents, robotics, egocentric video, games and spatial planning, for evaluating VLMs in agentic settings.
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主题与学科
同主题：评测与数据
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- PremiseCheck: Efficient Fact-Checking of Human and AI Peer Reviews ▲210
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- GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay ▲73
- More Choices, Fewer Decisions: Ordinal-Scale Bias in JEV-like Direct-Decision Models ▲65
同主题：多模态
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- MJev-Spatial: System One Spatial Intelligence via Native Attention Matching 2026-10-15 · ▲556
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- LoopVL: Recurrent Visual Intelligence 2026-09-29 · ▲417
- VideoJev: System One Model for Video Understanding and Interaction 2026-10-13 · ▲375
数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-26。
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