5 papers
SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model
Shiyue Cao, Pei Xu, Likun Yang +3
Accurately predicting opponents' behavior from interactions is a fundamental capability for large language model (LLM)-based agents in multi-agent and game-theoretic environments.…
Repeated Deceptive Path Planning against Learnable Observer
Shiyue Cao, Pei Xu, Likun Yang +6
We study the problem of deceptive path planning (DPP), where an agent aims to conceal its true destination from external observers. While existing work assumes static, non-learning…
VS-LLM: Visual-Semantic Depression Assessment based on LLM for Drawing Projection Test
Meiqi Wu, Yaxuan Kang, Xuchen Li +5
The Drawing Projection Test (DPT) is an essential tool in art therapy, allowing psychologists to assess participants' mental states through their sketches. Specifically, through sk…
ATCTrack: Aligning Target-Context Cues with Dynamic Target States for Robust Vision-Language Tracking
X. Feng, S. Hu, X. Li +5
Vision-language tracking aims to locate the target object in the video sequence using a template patch and a language description provided in the initial frame. To achieve robust t…
Enhancing Vision-Language Tracking by Effectively Converting Textual Cues into Visual Cues
X. Feng, D. Zhang, S. Hu +5
Vision-Language Tracking (VLT) aims to localize a target in video sequences using a visual template and language description. While textual cues enhance tracking potential, current…