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Guangtao Zhai

CVPR 2026×9ICLR 2026×5AAAI 2026×3ACL 2026×2多模态评测与基准智能体与工具可解释性强化学习与后训练
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合作网络12
0 一作 · 19 篇 · CVPR 2026 / ICLR 2026 / AAAI 2026 / ACL 2026

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2026 顶会论文

19
作者位次 #5/5ICLR 2026Poster· Computer Vision / Classification and Understanding

Steering and Rectifying Latent Representation Manifolds in Frozen Multi-modal LLMs for Video Anomaly Detection

Zhaolin Cai · Fan Li · Huiyu Duan · Lijun He · Guangtao Zhai

多模态可解释性OpenReview
作者位次 #8/8ACL 2026Poster· Natural Language Processing

One Battle After Another: Probing LLM s’ Limits on Multi-Turn Instruction Following with a Benchmark Evolving Framework

Qi Jia · Ye Shen · Xiujie Song · Kaiwei Zhang · Shibo Wang · Dun Pei · Xiangyang Zhu · Guangtao Zhai

摘要

Evaluating LLMs’ instruction-following ability in multi-topic dialogues is essential yet challenging. Existing benchmarks are limited to a fixed number of turns, susceptible to saturation and failing to account for users’ interactive experience. In this work, we propose a novel framework featurin...

可解释性评测与基准智能体与工具OpenReview 项目页
作者位次 #6/6ACL 2026Poster· Natural Language Processing

Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition

Yushuo Zheng · Huiyu Duan · Zicheng Zhang · Yucheng Zhu · Xiongkuo Min · Guangtao Zhai

摘要

The ability of large language models (LLMs) to manage and acquire economic resources remains unclear. In this paper, we introduce Market-Bench , a comprehensive benchmark that evaluates the capabilities of LLMs in economically-relevant tasks through economic and trade competition. Specifically, w...

智能体与工具评测与基准可解释性OpenReview 项目页

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