activity
20182022
most citedCharacterizing Bias in Classifiers using Generative Models

20 citations · 38 across the 10 of their papers we have counts for

collaborators

12 papers

cs.RO20224 cited

Reshaping Robot Trajectories Using Natural Language Commands: A Study of Multi-Modal Data Alignment Using Transformers

Arthur Bucker, Luis Figueredo, Sami Haddadin +3

Natural language is the most intuitive medium for us to interact with other people when expressing commands and instructions. However, using language is seldom an easy task when hu…

cs.RO2022

COMPASS: Contrastive Multimodal Pretraining for Autonomous Systems

Shuang Ma, Sai Vemprala, Wenshan Wang +4

Learning representations that generalize across tasks and domains is challenging yet necessary for autonomous systems. Although task-driven approaches are appealing, designing mode…

cs.CL20211 cited

A Neural Network-Based Linguistic Similarity Measure for Entrainment in Conversations

Mingzhi Yu, Diane Litman, Shuang Ma +1

Linguistic entrainment is a phenomenon where people tend to mimic each other in conversation. The core instrument to quantify entrainment is a linguistic similarity measure between…

cs.AI20215 cited

CausalCity: Complex Simulations with Agency for Causal Discovery and Reasoning

Daniel McDuff, Yale Song, Jiyoung Lee +7

The ability to perform causal and counterfactual reasoning are central properties of human intelligence. Decision-making systems that can perform these types of reasoning have the…

cs.LG2021

Contrastive Learning of Global-Local Video Representations

Shuang Ma, Zhaoyang Zeng, Daniel McDuff +1

Contrastive learning has delivered impressive results for various tasks in the self-supervised regime. However, existing approaches optimize for learning representations specific t…

cs.LG2020

Active Contrastive Learning of Audio-Visual Video Representations

Shuang Ma, Zhaoyang Zeng, Daniel McDuff +1

Contrastive learning has been shown to produce generalizable representations of audio and visual data by maximizing the lower bound on the mutual information (MI) between different…