42 citations · 249 across the 35 of their papers we have counts for
9 papers · 1 filter
CPL: Counterfactual Prompt Learning for Vision and Language Models
Xuehai He, Diji Yang, Weixi Feng +7
Prompt tuning is a new few-shot transfer learning technique that only tunes the learnable prompt for pre-trained vision and language models such as CLIP. However, existing prompt t…
ULN: Towards Underspecified Vision-and-Language Navigation
Weixi Feng, Tsu-Jui Fu, Yujie Lu +1
Vision-and-Language Navigation (VLN) is a task to guide an embodied agent moving to a target position using language instructions. Despite the significant performance improvement,…
Anticipating the Unseen Discrepancy for Vision and Language Navigation
Yujie Lu, Huiliang Zhang, Ping Nie +4
Vision-Language Navigation requires the agent to follow natural language instructions to reach a specific target. The large discrepancy between seen and unseen environments makes i…
L2C: Describing Visual Differences Needs Semantic Understanding of Individuals
An Yan, Xin Eric Wang, Tsu-Jui Fu +1
Recent advances in language and vision push forward the research of captioning a single image to describing visual differences between image pairs. Suppose there are two images, I_…
Learning to Stop: A Simple yet Effective Approach to Urban Vision-Language Navigation
Jiannan Xiang, Xin Eric Wang, William Yang Wang
Vision-and-Language Navigation (VLN) is a natural language grounding task where an agent learns to follow language instructions and navigate to specified destinations in real-world…
Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation
Juncheng Li, Xin Wang, Siliang Tang +4
Visual navigation is a task of training an embodied agent by intelligently navigating to a target object (e.g., television) using only visual observations. A key challenge for curr…