most citedCausalStock: Deep End-to-end Causal Discovery for News-driven Stock Movement Prediction

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2025

RoboDriveVLM: A Novel Benchmark and Baseline towards Robust Vision-Language Models for Autonomous Driving

Dacheng Liao, Mengshi Qi, Peng Shu +4

Current Vision-Language Model (VLM)-based end-to-end autonomous driving systems often leverage large language models to generate driving decisions directly based on their understan…

cs.CV2025

HairShifter: Consistent and High-Fidelity Video Hair Transfer via Anchor-Guided Animation

Wangzheng Shi, Yinglin Zheng, Yuxin Lin +3

Hair transfer is increasingly valuable across domains such as social media, gaming, advertising, and entertainment. While significant progress has been made in single-image hair tr…

cs.CL2025

Predicting Turn-Taking and Backchannel in Human-Machine Conversations Using Linguistic, Acoustic, and Visual Signals

Yuxin Lin, Yinglin Zheng, Ming Zeng +1

This paper addresses the gap in predicting turn-taking and backchannel actions in human-machine conversations using multi-modal signals (linguistic, acoustic, and visual). To overc…

cs.CV2025

VLM-Assisted Continual learning for Visual Question Answering in Self-Driving

Yuxin Lin, Mengshi Qi, Liang Liu +1

In this paper, we propose a novel approach for solving the Visual Question Answering (VQA) task in autonomous driving by integrating Vision-Language Models (VLMs) with continual le…

cs.LG20241 cited

CausalStock: Deep End-to-end Causal Discovery for News-driven Stock Movement Prediction

Shuqi Li, Yuebo Sun, Yuxin Lin +3

There are two issues in news-driven multi-stock movement prediction tasks that are not well solved in the existing works. On the one hand, "relation discovery" is a pivotal part wh…