11 citations · 16 across the 22 of their papers we have counts for
6 papers · 2 filters
Iris: Breaking GUI Complexity with Adaptive Focus and Self-Refining
Zhiqi Ge, Juncheng Li, Xinglei Pang +7
Digital agents are increasingly employed to automate tasks in interactive digital environments such as web pages, software applications, and operating systems. While text-based age…
STEP: Enhancing Video-LLMs' Compositional Reasoning by Spatio-Temporal Graph-guided Self-Training
Haiyi Qiu, Minghe Gao, Long Qian +7
Video Large Language Models (Video-LLMs) have recently shown strong performance in basic video understanding tasks, such as captioning and coarse-grained question answering, but st…
AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea
Qifan Yu, Wei Chow, Zhongqi Yue +7
Instruction-based image editing aims to modify specific image elements with natural language instructions. However, current models in this domain often struggle to accurately execu…
Unified Generative and Discriminative Training for Multi-modal Large Language Models
Wei Chow, Juncheng Li, Qifan Yu +7
In recent times, Vision-Language Models (VLMs) have been trained under two predominant paradigms. Generative training has enabled Multimodal Large Language Models (MLLMs) to tackle…
Towards Unified Multimodal Editing with Enhanced Knowledge Collaboration
Kaihang Pan, Zhaoyu Fan, Juncheng Li +6
The swift advancement in Multimodal LLMs (MLLMs) also presents significant challenges for effective knowledge editing. Current methods, including intrinsic knowledge editing and ex…
Auto-Encoding Morph-Tokens for Multimodal LLM
Kaihang Pan, Siliang Tang, Juncheng Li +6
For multimodal LLMs, the synergy of visual comprehension (textual output) and generation (visual output) presents an ongoing challenge. This is due to a conflicting objective: for…