activity
20242026
collaborators

8 papers

cs.CV2026

Reasoning-Aligned Perception Decoupling for Scalable Multi-modal Reasoning

Yunhao Gou, Kai Chen, Zhili Liu +5

Recent breakthroughs in reasoning language models have significantly advanced text-based reasoning. On the other hand, Multi-modal Large Language Models (MLLMs) still lag behind, h…

cs.CV2025

MagicDrive-V2: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Control

Ruiyuan Gao, Kai Chen, Bo Xiao +3

The rapid advancement of diffusion models has greatly improved video synthesis, especially in controllable video generation, which is vital for applications like autonomous driving…

cs.CV2025

MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes

Ruiyuan Gao, Kai Chen, Zhihao Li +3

Controllable generative models for images and videos have seen significant success, yet 3D scene generation, especially in unbounded scenarios like autonomous driving, remains unde…

cs.CV2025

ECCV 2024 W-CODA: 1st Workshop on Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving

Kai Chen, Ruiyuan Gao, Lanqing Hong +11

In this paper, we present details of the 1st W-CODA workshop, held in conjunction with the ECCV 2024. W-CODA aims to explore next-generation solutions for autonomous driving corner…

cs.CL2025

Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment

Zhili Liu, Yunhao Gou, Kai Chen +8

As the capabilities of large language models (LLMs) continue to expand, aligning these models with human values remains a significant challenge. Recent studies show that reasoning…

cs.CV2025

Corrupted but Not Broken: Understanding and Mitigating the Negative Impacts of Corrupted Data in Visual Instruction Tuning

Yunhao Gou, Hansi Yang, Zhili Liu +8

Visual Instruction Tuning (VIT) aims to enhance Multimodal Large Language Models (MLLMs), yet its effectiveness is often compromised by corrupted datasets with issues such as hallu…