collaborators

17 papers

cs.CL2026

CausalGame: Benchmarking Causal Thinking of LLM Agents in Games

Zhenhao Chen, Yongqiang Chen, Chenxi Liu +7

Building AI Scientist agents with Large Language Models (LLMs) has recently attracted growing attention. Since scientific discovery fundamentally relies on uncovering causal relati…

cs.CV2026

MoVA: Learning Asymmetric Dual Projections for Modular Long Video-Text Alignment

Peiyuan Zhu, Shaoan Xie, Zijian Li +5

Contrastive pre-training has propelled video-text alignment, yet models often inherit the critical limitations of their image-text predecessors like CLIP, resulting in entangled re…

cs.LG2026

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

Minghao Fu, Biwei Huang, Zijian Li +5

Understanding climate dynamics requires going beyond correlations in observational data to uncover the underlying causal process. Latent drivers such as atmospheric processes play…

cs.LG2026

Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making

Fan Feng, Selena Ge, Minghao Fu +6

Recent work has framed decision-making as a sequence modeling problem using generative models such as diffusion models. Although promising, these approaches often overlook latent f…

cs.LG2026

A General Representation-Based Approach to Multi-Source Domain Adaptation

Ignavier Ng, Yan Li, Zijian Li +3

A central problem in unsupervised domain adaptation is determining what to transfer from labeled source domains to an unlabeled target domain. To handle high-dimensional observatio…

cs.LG2026

Diverse Dictionary Learning

Yujia Zheng, Zijian Li, Shunxing Fan +2

Given only observational data , where both the latent variables and the generating process are unknown, recovering is ill-posed without additional assumptions…