565 citations · 1.7k across the 68 of their papers we have counts for
8 papers · 1 filter
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
Paul Pu Liang, Yiwei Lyu, Xiang Fan +9
Learning multimodal representations involves integrating information from multiple heterogeneous sources of data. It is a challenging yet crucial area with numerous real-world appl…
Towards Understanding and Mitigating Social Biases in Language Models
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency +1
As machine learning methods are deployed in real-world settings such as healthcare, legal systems, and social science, it is crucial to recognize how they shape social biases and s…
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data
Paul Pu Liang, Terrance Liu, Anna Cai +7
Mental health conditions remain underdiagnosed even in countries with common access to advanced medical care. The ability to accurately and efficiently predict mood from easily col…
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning
Liangqiong Qu, Yuyin Zhou, Paul Pu Liang +5
Federated learning is an emerging research paradigm enabling collaborative training of machine learning models among different organizations while keeping data private at each inst…
Conditional Contrastive Learning for Improving Fairness in Self-Supervised Learning
Martin Q. Ma, Yao-Hung Hubert Tsai, Paul Pu Liang +4
Contrastive self-supervised learning (SSL) learns an embedding space that maps similar data pairs closer and dissimilar data pairs farther apart. Despite its success, one issue has…
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…
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…
Understanding the Tradeoffs in Client-side Privacy for Downstream Speech Tasks
Peter Wu, Paul Pu Liang, Jiatong Shi +3
As users increasingly rely on cloud-based computing services, it is important to ensure that uploaded speech data remains private. Existing solutions rely either on server-side met…