activity
20232025
most citedUnified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization

3 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Group Relative Attention Guidance for Image Editing

Xuanpu Zhang, Xuesong Niu, Ruidong Chen +6

Recently, image editing based on Diffusion-in-Transformer models has undergone rapid development. However, existing editing methods often lack effective control over the degree of…

cs.RO2025★ 1 cited

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios

Huaiyuan Yao, Pengfei Li, Bu Jin +7

Recent advances in autonomous driving research towards motion planners that are robust, safe, and adaptive. However, existing rule-based and data-driven planners lack adaptability…

cs.CL2024

LEGENT: Open Platform for Embodied Agents

Zhili Cheng, Zhitong Wang, Jinyi Hu +7

Despite advancements in Large Language Models (LLMs) and Large Multimodal Models (LMMs), their integration into language-grounded, human-like embodied agents remains incomplete, hi…

cs.AI2024

Towards Unified Alignment Between Agents, Humans, and Environment

Zonghan Yang, An Liu, Zijun Liu +11

The rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of foundation models to conduct reasoning, decisio…

cs.CL2024

PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs

An Liu, Zonghan Yang, Zhenhe Zhang +6

While Large language models (LLMs) have demonstrated considerable capabilities across various natural language tasks, they often fall short of the performance achieved by domain-sp…

cs.CV2023★ 3 cited

Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization

Yang Jin, Kun Xu, Liwei Chen +12

Recently, the remarkable advance of the Large Language Model (LLM) has inspired researchers to transfer its extraordinary reasoning capability to both vision and language data. How…