8 papers
Chem4DLLM: 4D Multimodal LLMs for Chemical Dynamics Understanding
Xinyu Li, Zhen Zhang, Qi Chen +3
Existing chemical understanding tasks primarily rely on static molecular representations, limiting their ability to model inherently dynamic phenomena such as bond breaking or conf…
Learning to Retrieve Navigable Candidates for Efficient Vision-and-Language Navigation
Shutian Gu, Chengkai Huang, Ruoyu Wang +1
Vision-and-Language Navigation (VLN) requires an agent to follow natural-language instructions and navigate through previously unseen environments. Recent approaches increasingly e…
Weakly-supervised VLM-guided Partial Contrastive Learning for Visual Language Navigation
Ruoyu Wang, Tong Yu, Junda Wu +3
Visual Language Navigation (VLN) is a fundamental task within the field of Embodied AI, focusing on the ability of agents to navigate complex environments based on natural language…
Efficient and Generalizable Environmental Understanding for Visual Navigation
Ruoyu Wang, Xinshu Li, Chen Wang +1
Visual Navigation is a core task in Embodied AI, enabling agents to navigate complex environments toward given objectives. Across diverse settings within Navigation tasks, many nec…
Regularized Multi-LLMs Collaboration for Enhanced Score-based Causal Discovery
Xiaoxuan Li, Yao Liu, Ruoyu Wang +1
As the significance of understanding the cause-and-effect relationships among variables increases in the development of modern systems and algorithms, learning causality from obser…
Deconfounded Causality-aware Parameter-Efficient Fine-Tuning for Problem-Solving Improvement of LLMs
Ruoyu Wang, Xiaoxuan Li, Lina Yao
Large Language Models (LLMs) have demonstrated remarkable efficiency in tackling various tasks based on human instructions, but studies reveal that they often struggle with tasks r…