12 citations · 30 across the 8 of their papers we have counts for
10 papers
English Contrastive Learning Can Learn Universal Cross-lingual Sentence Embeddings
Yau-Shian Wang, Ashley Wu, Graham Neubig
Universal cross-lingual sentence embeddings map semantically similar cross-lingual sentences into a shared embedding space. Aligning cross-lingual sentence embeddings usually requi…
Toxicity Detection with Generative Prompt-based Inference
Yau-Shian Wang, Yingshan Chang
Due to the subtleness, implicity, and different possible interpretations perceived by different people, detecting undesirable content from text is a nuanced difficulty. It is a lon…
Long-tailed Extreme Multi-label Text Classification with Generated Pseudo Label Descriptions
Ruohong Zhang, Yau-Shian Wang, Yiming Yang +3
Extreme Multi-label Text Classification (XMTC) has been a tough challenge in machine learning research and applications due to the sheer sizes of the label spaces and the severe da…
Exploiting Local and Global Features in Transformer-based Extreme Multi-label Text Classification
Ruohong Zhang, Yau-Shian Wang, Yiming Yang +2
Extreme multi-label text classification (XMTC) is the task of tagging each document with the relevant labels from a very large space of predefined categories. Recently, large pre-t…
Are you doing what I say? On modalities alignment in ALFRED
Ting-Rui Chiang, Yi-Ting Yeh, Ta-Chung Chi +1
ALFRED is a recently proposed benchmark that requires a model to complete tasks in simulated house environments specified by instructions in natural language. We hypothesize that k…
Investigation of Sentiment Controllable Chatbot
Hung-yi Lee, Cheng-Hao Ho, Chien-Fu Lin +5
Conventional seq2seq chatbot models attempt only to find sentences with the highest probabilities conditioned on the input sequences, without considering the sentiment of the outpu…