activity
20232026
most citedRethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes

9 citations · 9 across the 5 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Copper-Policy: Focus on the Representation for Robust Robot Manipulation

Zexin Feng, Yixu Feng, Lingyu Xiao +6

World Action Models (WAMs) acquire behavioral priors by modeling future scene evolution, but predicting detailed futures in pixel or latent space incurs substantial cost. Recent ev…

cs.AI2026

Long-term Traffic Simulation via Structured Autoregressive Modeling

Lingyu Xiao, Zexin Feng, Xintao Yan

Interactive traffic simulation is a vital world model for autonomous driving. A central challenge in long-horizon simulation is modeling sustained multi-agent interactions, which i…

cs.AI2026

MagicAgent: Towards Generalized Agent Planning

Xuhui Ren, Shaokang Dong, Chen Yang +21

The evolution of Large Language Models (LLMs) from passive text processors to autonomous agents has established planning as a core component of modern intelligence. However, achiev…

cs.CV2025

EM-KD: Distilling Efficient Multimodal Large Language Model with Unbalanced Vision Tokens

Ze Feng, Sen Yang, Boqiang Duan +2

Efficient Multimodal Large Language Models (MLLMs) compress vision tokens to reduce resource consumption, but the loss of visual information can degrade comprehension capabilities.…

cs.CV2025

Vision Remember: Recovering Visual Information in Efficient LVLM with Vision Feature Resampling

Ze Feng, Jiang-jiang Liu, Sen Yang +5

The computational expense of redundant vision tokens in Large Vision-Language Models (LVLMs) has led many existing methods to compress them via a vision projector. However, this co…

cs.CV2024

Revisiting MLLMs: An In-Depth Analysis of Image Classification Abilities

Huan Liu, Lingyu Xiao, Jiangjiang Liu +4

With the rapid advancement of Multimodal Large Language Models (MLLMs), a variety of benchmarks have been introduced to evaluate their capabilities. While most evaluations have foc…

cs.CV2023★ 9 cited

Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes

Jiang-Tian Zhai, Ze Feng, Jinhao Du +6

Modern autonomous driving systems are typically divided into three main tasks: perception, prediction, and planning. The planning task involves predicting the trajectory of the ego…