3 citations · 5 across the 5 of their papers we have counts for
10 papers
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,…
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_…
H-FND: Hierarchical False-Negative Denoising for Distant Supervision Relation Extraction
Jhih-Wei Chen, Tsu-Jui Fu, Chen-Kang Lee +1
Although distant supervision automatically generates training data for relation extraction, it also introduces false-positive (FP) and false-negative (FN) training instances to the…
Multimodal Text Style Transfer for Outdoor Vision-and-Language Navigation
Wanrong Zhu, Xin Eric Wang, Tsu-Jui Fu +5
One of the most challenging topics in Natural Language Processing (NLP) is visually-grounded language understanding and reasoning. Outdoor vision-and-language navigation (VLN) is s…
Why Attention? Analyzing and Remedying BiLSTM Deficiency in Modeling Cross-Context for NER
Peng-Hsuan Li, Tsu-Jui Fu, Wei-Yun Ma
State-of-the-art approaches of NER have used sequence-labeling BiLSTM as a core module. This paper formally shows the limitation of BiLSTM in modeling cross-context patterns. Two t…