7 citations · 14 across the 4 of their papers we have counts for
5 papers
Towards Debiasing Sentence Representations
Paul Pu Liang, Irene Mengze Li, Emily Zheng +3
As natural language processing methods are increasingly deployed in real-world scenarios such as healthcare, legal systems, and social science, it becomes necessary to recognize th…
Pseudo-Encoded Stochastic Variational Inference
Amir Zadeh, Smon Hessner, Yao-Chong Lim +1
Posterior inference in directed graphical models is commonly done using a probabilistic encoder (a.k.a inference model) conditioned on the input. Often this inference model is trai…
Strong and Simple Baselines for Multimodal Utterance Embeddings
Paul Pu Liang, Yao Chong Lim, Yao-Hung Hubert Tsai +2
Human language is a rich multimodal signal consisting of spoken words, facial expressions, body gestures, and vocal intonations. Learning representations for these spoken utterance…
Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings
Thomas Manzini, Yao Chong Lim, Yulia Tsvetkov +1
Online texts -- across genres, registers, domains, and styles -- are riddled with human stereotypes, expressed in overt or subtle ways. Word embeddings, trained on these texts, per…
Variational Auto-Decoder: A Method for Neural Generative Modeling from Incomplete Data
Amir Zadeh, Yao-Chong Lim, Paul Pu Liang +1
Learning a generative model from partial data (data with missingness) is a challenging area of machine learning research. We study a specific implementation of the Auto-Encoding Va…