activity
20192023
most citedELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders

18 citations · 57 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2023★ 18 cited

ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders

Shawn Xu, Lin Yang, Christopher Kelly +25

In this work, we present an approach, which we call Embeddings for Language/Image-aligned X-Rays, or ELIXR, that leverages a language-aligned image encoder combined or grafted onto…

cs.LG2023★ 2 cited

Understanding Masked Autoencoders via Hierarchical Latent Variable Models

Lingjing Kong, Martin Q. Ma, Guangyi Chen +4

Masked autoencoder (MAE), a simple and effective self-supervised learning framework based on the reconstruction of masked image regions, has recently achieved prominent success in…

cs.LG2023★ 15 cited

Factorized Contrastive Learning: Going Beyond Multi-view Redundancy

Paul Pu Liang, Zihao Deng, Martin Ma +3

In a wide range of multimodal tasks, contrastive learning has become a particularly appealing approach since it can successfully learn representations from abundant unlabeled data…

cs.LG2022

Face-to-Face Contrastive Learning for Social Intelligence Question-Answering

Alex Wilf, Martin Q. Ma, Paul Pu Liang +2

Creating artificial social intelligence - algorithms that can understand the nuances of multi-person interactions - is an exciting and emerging challenge in processing facial expre…

cs.LG2022★ 5 cited

Conditional Contrastive Learning with Kernel

Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma +4

Conditional contrastive learning frameworks consider the conditional sampling procedure that constructs positive or negative data pairs conditioned on specific variables. Fair cont…

cs.LG2021★ 5 cited

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…

cs.LG2021★ 5 cited

A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice?

Martin Q. Ma, Yue Zhao, Xiaorong Zhang +1

Given an unsupervised outlier detection task, how should one select a detection algorithm as well as its hyperparameters (jointly called a model)? Unsupervised model selection is n…

cs.LG2021★ 4 cited

Self-supervised Representation Learning with Relative Predictive Coding

Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang +3

This paper introduces Relative Predictive Coding (RPC), a new contrastive representation learning objective that maintains a good balance among training stability, minibatch size s…

cs.CL2020

Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis

Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang +2

The human language can be expressed through multiple sources of information known as modalities, including tones of voice, facial gestures, and spoken language. Recent multimodal l…

cs.LG2019★ 3 cited

Complex Transformer: A Framework for Modeling Complex-Valued Sequence

Muqiao Yang, Martin Q. Ma, Dongyu Li +2

While deep learning has received a surge of interest in a variety of fields in recent years, major deep learning models barely use complex numbers. However, speech, signal and audi…