works on

From the 1 of 7 linked papers with an AI index.

most citedfMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

Xiangning Lin, Shenzhe Zhu, Shu Yang +23

The paper presents AISPA, a user‑centric framework for auditing the system prompts that guide large language model behavior in commercial AI products, and reports findings from ana…

cs.RO2026

Progress Reward Modeling for Robotic Learning: A Comprehensive Survey

Jianshu Zhang, Keliang Wu, Haoran Lu +8

Robotic learning takes place in dynamic environments with large behavior spaces. A terminal success signal only tells the robot whether the task is completed. It does not explain w…

cs.CV2026

PROGRESSLM: Towards Progress Reasoning in Vision-Language Models

Jianshu Zhang, Chengxuan Qian, Haosen Sun +4

Estimating task progress requires reasoning over long-horizon dynamics rather than recognizing static visual content. While modern Vision-Language Models (VLMs) excel at describing…

cs.CV2026

What if Agents Could Imagine? Reinforcing Open-Vocabulary HOI Comprehension through Generation

Zhenlong Yuan, Yue Wang, Dapeng Zhang +9

Multimodal Large Language Models have shown promising capabilities in bridging visual and textual reasoning, yet their reasoning capabilities in Open-Vocabulary Human-Object Intera…

cs.CL20261 cited

fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding

Yuxiang Wei, Yanteng Zhang, Xi Xiao +3

Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capability to brain imaging remains la…

cs.RO2026

AutoDrive-R: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving

Zhenlong Yuan, Chengxuan Qian, Jing Tang +7

Vision-Language-Action (VLA) models in autonomous driving systems have recently demonstrated transformative potential by integrating multimodal perception with decision-making capa…