5 papers
GUI-AC: Enhancing Continual Learning in GUI Agents
Can Lin, Tao Feng, Hangjie Yuan +3
Graphical User Interfaces (GUIs) serve as the dominant medium for human-computer interaction, yet building GUI agents that generalize across the vast diversity of real-world interf…
5% > 100%: Flatness Preference is All You Need for Multimodal Parameter-Efficient Fine-Tuning
Yifan Zhu, Can Lin, Hangjie Yuan +4
Parameter-Efficient Fine-Tuning (PEFT) methods provide a streamlined and efficient tool for adapting large models to domain-specific multimodal downstream tasks. Although these met…
ERGeoBench:A Comprehensive Benchmark for Embodied Reasoning and Geo-localization in Multimodal Large Language Models
Kaiwen Xue, Tao Wei, Guoxin Zhang +5
Multimodal large language models (MLLMs) have shown strong potential as embodied agents, yet embodied geo-localization remains underexplored due to the lack of fine-grained evaluat…
Efficient Robotic Policy Learning via Latent Space Backward Planning
Dongxiu Liu, Haoyi Niu, Zhihao Wang +6
Current robotic planning methods often rely on predicting multi-frame images with full pixel details. While this fine-grained approach can serve as a generic world model, it introd…
Universal Actions for Enhanced Embodied Foundation Models
Jinliang Zheng, Jianxiong Li, Dongxiu Liu +7
Training on diverse, internet-scale data is a key factor in the success of recent large foundation models. Yet, using the same recipe for building embodied agents has faced noticea…