activity
20232026
most citedImageBind-LLM: Multi-modality Instruction Tuning

25 citations · 28 across the 15 of their papers we have counts for

collaborators

16 papers

cs.CL2026

ToolLoop: Closed-Loop Tool-Use Data Synthesis via Decomposed Generation and Dynamic Self-Feedback

Min Zeng, Yuzhou Liu, Zhenyu Cao +5

High-quality tool-use data is critical for training language models to interact effectively with external tools. However, existing synthetic approaches typically follow a generate-…

cs.CL2026

VISA: Agentic Self-Evolving Data Synthesis for Multimodal Instruction Following

Min Zeng, Guanxin Tan, Libin Cen +5

Multimodal instruction-following models require training data that is accurate, diverse, verifiable, and challenging. Existing synthesis pipelines typically follow a one-pass gener…

cs.CV2026

Plans You Can Check: Verifier-Grounded Learning of an Open-Weight Planner for Executable Video-Editing

Haoyu Wang, Cheng Feng, Liuyang Bian +5

Practical video editing is not only pixel generation: an editor must turn a brief, a clip pool, music metadata, and hard constraints into an executable timeline. We study this deci…

cs.LG2026

SOLAR-RL: Semi-Online Long-horizon Assignment Reinforcement Learning

Jichao Wang, Liuyang Bian, Yufeng Zhou +9

As Multimodal Large Language Models (MLLMs) mature, GUI agents are evolving from static interactions to complex navigation. While Reinforcement Learning (RL) has emerged as a promi…

cs.LG2026

Skill-SD: Skill-Conditioned Self-Distillation for Multi-turn LLM Agents

Hao Wang, Guozhi Wang, Han Xiao +8

Reinforcement learning (RL) has been widely used to train LLM agents for multi-turn interactive tasks, but its sample efficiency is severely limited by sparse rewards and long hori…

cs.CV2026

UI-Mem: Self-Evolving Experience Memory for Online Reinforcement Learning in Mobile GUI Agents

Han Xiao, Guozhi Wang, Hao Wang +7

Online Reinforcement Learning (RL) offers a promising paradigm for enhancing GUI agents through direct environment interaction. However, its effectiveness is severely hindered by i…

cs.CV2025

VideoChat-M1: Collaborative Policy Planning for Video Understanding via Multi-Agent Reinforcement Learning

Boyu Chen, Zikang Wang, Zhengrong Yue +9

By leveraging tool-augmented Multimodal Large Language Models (MLLMs), multi-agent frameworks are driving progress in video understanding. However, most of them adopt static and no…

cs.AI2025

BlueLM-2.5-3B Technical Report

Baojiao Xiong, Boheng Chen, Chengzhi Wang +58

We present BlueLM-2.5-3B, a compact and unified dense Multimodal Large Language Model (MLLM) designed for efficient edge-device deployment, offering strong general-purpose and reas…

cs.CL2025

UI-Genie: A Self-Improving Approach for Iteratively Boosting MLLM-based Mobile GUI Agents

Han Xiao, Guozhi Wang, Yuxiang Chai +12

In this paper, we introduce UI-Genie, a self-improving framework addressing two key challenges in GUI agents: verification of trajectory outcome is challenging and high-quality tra…

cs.CV2025

Adaptive Markup Language Generation for Contextually-Grounded Visual Document Understanding

Han Xiao, Yina Xie, Guanxin Tan +12

Visual Document Understanding has become essential with the increase of text-rich visual content. This field poses significant challenges due to the need for effective integration…

cs.CL2025

GenieBlue: Integrating both Linguistic and Multimodal Capabilities for Large Language Models on Mobile Devices

Xudong Lu, Yinghao Chen, Renshou Wu +10

Recent advancements in Multimodal Large Language Models (MLLMs) have enabled their deployment on mobile devices. However, challenges persist in maintaining strong language capabili…

cs.CV2024

BlueLM-V-3B: Algorithm and System Co-Design for Multimodal Large Language Models on Mobile Devices

Xudong Lu, Yinghao Chen, Cheng Chen +19

The emergence and growing popularity of multimodal large language models (MLLMs) have significant potential to enhance various aspects of daily life, from improving communication t…

cs.CV2024

TerDiT: Ternary Diffusion Models with Transformers

Xudong Lu, Aojun Zhou, Ziyi Lin +7

Recent developments in large-scale pre-trained text-to-image diffusion models have significantly improved the generation of high-fidelity images, particularly with the emergence of…

cs.CV2023★ 1 cited

GPT4Motion: Scripting Physical Motions in Text-to-Video Generation via Blender-Oriented GPT Planning

Jiaxi Lv, Yi Huang, Mingfu Yan +6

Recent advances in text-to-video generation have harnessed the power of diffusion models to create visually compelling content conditioned on text prompts. However, they usually en…

cs.MM2023★ 25 cited

ImageBind-LLM: Multi-modality Instruction Tuning

Jiaming Han, Renrui Zhang, Wenqi Shao +14

We present ImageBind-LLM, a multi-modality instruction tuning method of large language models (LLMs) via ImageBind. Existing works mainly focus on language and image instruction tu…

cs.CV2023★ 2 cited

Real-Time Image Demoireing on Mobile Devices

Yuxin Zhang, Mingbao Lin, Xunchao Li +7

Moire patterns appear frequently when taking photos of digital screens, drastically degrading the image quality. Despite the advance of CNNs in image demoireing, existing networks…