most citedExplain Any Concept: Segment Anything Meets Concept-Based Explanation

10 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV202310 cited

Explain Any Concept: Segment Anything Meets Concept-Based Explanation

Ao Sun, Pingchuan Ma, Yuanyuan Yuan +1

EXplainable AI (XAI) is an essential topic to improve human understanding of deep neural networks (DNNs) given their black-box internals. For computer vision tasks, mainstream pixe…

cs.SE20236 cited

"Oops, Did I Just Say That?" Testing and Repairing Unethical Suggestions of Large Language Models with Suggest-Critique-Reflect Process

Pingchuan Ma, Zongjie Li, Ao Sun +1

As the popularity of large language models (LLMs) soars across various applications, ensuring their alignment with human values has become a paramount concern. In particular, given…

cs.CV20233 cited

SynthVSR: Scaling Up Visual Speech Recognition With Synthetic Supervision

Xubo Liu, Egor Lakomkin, Konstantinos Vougioukas +9

Recently reported state-of-the-art results in visual speech recognition (VSR) often rely on increasingly large amounts of video data, while the publicly available transcribed video…

cs.RO20234 cited

SoftZoo: A Soft Robot Co-design Benchmark For Locomotion In Diverse Environments

Tsun-Hsuan Wang, Pingchuan Ma, Andrew Everett Spielberg +5

While significant research progress has been made in robot learning for control, unique challenges arise when simultaneously co-optimizing morphology. Existing work has typically b…

cs.CL2023

Learning Cross-lingual Visual Speech Representations

Andreas Zinonos, Alexandros Haliassos, Pingchuan Ma +2

Cross-lingual self-supervised learning has been a growing research topic in the last few years. However, current works only explored the use of audio signals to create representati…