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Home/Authors/Hong Hu

Hong Hu

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

AI×2Robotics×1NLP×1Crypto×1

Frequent co-authors

Qiuyue Wang1×
Mingsheng Li1×
Jian Guan1×
Jinhui Ye1×
Sicheng Xie1×
Yitao Liu1×

Research Timeline

2026
TRUSTDESC: Preventing Tool Poisoning in LLM Applications via Trusted Description Generation

The paper introduces TRUSTDESC, a novel framework that prevents tool poisoning attacks in LLM applications by automatically generating highly accurate and trusted tool descriptions directly from the tool's source code and behavior.

Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Qwen-VLA introduces a unified embodied foundation model that extends vision-language understanding to continuous action generation, enabling robust, multi-task generalization across diverse robotic tasks and embodiments.

PTCG-Bench: Can LLM Agents Master Pokémon Trading Card Game?

The paper introduces PTCG-Bench, a new benchmark using the Pokémon TCG to evaluate LLM agents' strategic decision-making and ability to self-evolve, finding that sustained self-evolution remains challenging.

Highlighted terms show continued research focus across papers

Papers

cs.ROcs.AIcs.CLRecentMay 28, 2026

Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Qiuyue Wang, Mingsheng Li, Jian Guan, Jinhui Ye +36 more

Qwen-VLA introduces a unified embodied foundation model that extends vision-language understanding to continuous action generation, enabling robust, multi-task generalization across diverse robotic ta…

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cs.AIRecentMay 28, 2026

PTCG-Bench: Can LLM Agents Master Pokémon Trading Card Game?

Dongdong Hua, Yifei Sun, Renhong Huang, Feng Gao +2 more

The paper introduces PTCG-Bench, a new benchmark using the Pokémon TCG to evaluate LLM agents' strategic decision-making and ability to self-evolve, finding that sustained self-evolution remains chall…

View →
cs.CRRecentApr 8, 2026

TRUSTDESC: Preventing Tool Poisoning in LLM Applications via Trusted Description Generation

Hengkai Ye, Zhechang Zhang, Jinyuan Jia, Hong Hu

The paper introduces TRUSTDESC, a novel framework that prevents tool poisoning attacks in LLM applications by automatically generating highly accurate and trusted tool descriptions directly from the t…

View →