1 citations · 3 across the 15 of their papers we have counts for
5 papers · 1 filter
DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer
Ruoyu Wang, Junda Wu, Yu Xia +4
Large language model-based agents, empowered by in-context learning (ICL), have demonstrated strong capabilities in complex reasoning and tool-use tasks. However, existing works ha…
Causality-aligned Prompt Learning via Diffusion-based Counterfactual Generation
Xinshu Li, Ruoyu Wang, Erdun Gao +2
Prompt learning has garnered attention for its efficiency over traditional model training and fine-tuning. However, existing methods, constrained by inadequate theoretical foundati…
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…
Mitigating Visual Knowledge Forgetting in MLLM Instruction-tuning via Modality-decoupled Gradient Descent
Junda Wu, Yuxin Xiong, Xintong Li +9
Recent MLLMs have shown emerging visual understanding and reasoning abilities after being pre-trained on large-scale multimodal datasets. Unlike pre-training, where MLLMs receive r…