Bang An
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Hi, I'm Bang!
I am a fifth-year PhD candidate in Computer Science at University of Maryland. I'm very fortunate to be advised by Prof. Furong Huang and work on Machine Learning as a member of UMIACS. Before coming to UMD, I was a research staff member at IBM Research China. I received my bachelor’s degree from Northeastern University (China) and my master’s degree from Tsinghua University.
My research focuses on Responsible AI. I am particularly interested in understanding and improving the safety, alignment, robustness, fairness, and interpretability of Generative AI. I believe that reliable machine learning is a critical element in enabling AI to better serve and support humanity.
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News
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RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models
Bang An, Shiyue Zhang, Mark Dredze
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GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-time Alignment
Yuancheng Xu, Udari Madhushani Sehwag, Alec Koppel, Sicheng Zhu, Bang An, Furong Huang, Sumitra Ganesh
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Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data?
Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang
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Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models
Bang An*, Sicheng Zhu*, Ruiyi Zhang, Michael-Andrei Panaitescu-Liess, Yuancheng Xu, Furong Huang
COLM 2024.
[Website]
[Code]
[Dataset]
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AutoDAN: Automatic and Interpretable Adversarial Attacks on Large Language Models
Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Zichao Wang, Furong Huang, Ani Nenkova, Tong Sun
COLM 2024.
[Website]
[Code]
[Media Coverage]
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Explore Spurious Correlations at the Concept Level in Language Models for Text Classification
Yuhang Zhou, Paiheng Xu, Xiaoyu Liu, Bang An, Wei Ai, Furong Huang
ACL 2024.
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WAVES: Benchmarking the Robustness of Image Watermarks
Bang An*, Mucong Ding*, Tahseen Rabbani*, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang
ICML 2024.
[Website]
[Code]
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Position: On the Possibilities of AI-Generated Text Detection
Souradip Chakraborty*, Amrit Singh Bedi*, Sicheng Zhu, Bang An, Dinesh Manocha, Furong Huang
ICML 2024.
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PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts
Bang An*, Sicheng Zhu*, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang
ICLR 2024.
[Code]
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SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation
Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang
ICLR 2024.
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Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator
Sicheng Zhu, Bang An, Furong Huang, Sanghyun Hong.
ICML 2023.
[Code]
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Transferring Fairness under Distribution Shifts via Fair Consistency Regularization
Bang An, Zora Che, Mucong Ding, Furong Huang.
NeurIPS 2022.
[Code]
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Understanding the Generalization Benefit of Model Invariance from a Data Perspective
Sicheng Zhu*, Bang An*, Furong Huang.
NeurIPS 2021.
[Code]
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Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference
Bang An, Jie Lyu, Zhenyi Wang, Chunyuan Li, Changwei Hu, Fei Tan, Ruiyi Zhang, Yifan Hu and Changyou Chen
EMNLP 2020.
[Code]
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Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints
Zhenyi Wang, Xiaoyang Wang, Bang An, Dong Yu, Changyou Chen
ACL 2020.
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Awards
- COLM 2024 DEI Travel Scholarship
- Outstanding Graduate Assistant Award of UMD (top 2%), 2023.
- NeurIPS 2022 Travel Award
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Services
- Reviewer: ICML 2022, NeurIPS 2022, ICML 2023, NeurIPS 2023, ICLR 2024, NAACL 2024
- Organizer: NeurIPS 2024 Competition, Erasing the Invisible: A Stress-Test Challenge for Image Watermarks.
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