activity
20182021
most citedFactorized Multimodal Transformer for Multimodal Sequential Learning

37 citations · 67 across the 9 of their papers we have counts for

collaborators

28 papers

cs.LG2021

Ask & Explore: Grounded Question Answering for Curiosity-Driven Exploration

Jivat Neet Kaur, Yiding Jiang, Paul Pu Liang

In many real-world scenarios where extrinsic rewards to the agent are extremely sparse, curiosity has emerged as a useful concept providing intrinsic rewards that enable the agent…

cs.CL2021

StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer

Yiwei Lyu, Paul Pu Liang, Hai Pham +4

Text style transfer aims to controllably generate text with targeted stylistic changes while maintaining core meaning from the source sentence constant. Many of the existing style…

cs.LG2020

Cross-Modal Generalization: Learning in Low Resource Modalities via Meta-Alignment

Paul Pu Liang, Peter Wu, Liu Ziyin +2

The natural world is abundant with concepts expressed via visual, acoustic, tactile, and linguistic modalities. Much of the existing progress in multimodal learning, however, focus…

cs.LG20205 cited

Multimodal Privacy-preserving Mood Prediction from Mobile Data: A Preliminary Study

Terrance Liu, Paul Pu Liang, Michal Muszynski +5

Mental health conditions remain under-diagnosed even in countries with common access to advanced medical care. The ability to accurately and efficiently predict mood from easily co…

cs.LG2020

An Investigation of how Label Smoothing Affects Generalization

Blair Chen, Liu Ziyin, Zihao Wang +1

It has been hypothesized that label smoothing can reduce overfitting and improve generalization, and current empirical evidence seems to corroborate these effects. However, there i…

cs.CL20207 cited

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…