activity
20232026
most citedReason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Towards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization

Ming Nie, Chunwei Wang, Jianhua Han +2

Unified vision-language models have made significant progress in multimodal understanding and generation, yet they largely fall short in producing multimodal interleaved outputs, w…

cs.CV2026

SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM

Ming Nie, Dan Ding, Chunwei Wang +4

Large language models (LLMs) have demonstrated exceptional capabilities in text understanding, which has paved the way for their expansion into video LLMs (Vid-LLMs) to analyze vid…

cs.CV2025

KFFocus: Highlighting Keyframes for Enhanced Video Understanding

Ming Nie, Chunwei Wang, Hang Xu +1

Recently, with the emergence of large language models, multimodal LLMs have demonstrated exceptional capabilities in image and video modalities. Despite advancements in video compr…

cs.CR2025

CipherMind: The Longest Codebook in the World

Ming Nie, Zhixiong Yang, Bingsheng Wei

In recent years, the widespread application of large language models has inspired us to consider using inference for communication encryption. We therefore propose CipherMind, whic…

cs.CV2024

LaneCorrect: Self-supervised Lane Detection

Ming Nie, Xinyue Cai, Hang Xu +1

Lane detection has evolved highly functional autonomous driving system to understand driving scenes even under complex environments. In this paper, we work towards developing a gen…

cs.CV2023★ 2 cited

Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving

Ming Nie, Renyuan Peng, Chunwei Wang +4

Large vision-language models (VLMs) have garnered increasing interest in autonomous driving areas, due to their advanced capabilities in complex reasoning tasks essential for highl…