Bang An

Affiliations:
  • University of Maryland, College Park, MD, USA


According to our database1, Bang An authored at least 20 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2021
2022
2023
2024
0
5
10
6
4
5
2
2
1

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine.
CoRR, 2024

GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-time Alignment.
CoRR, 2024

Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models.
CoRR, 2024

Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data?
CoRR, 2024

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.
CoRR, 2024

Benchmarking the Robustness of Image Watermarks.
CoRR, 2024

Position: On the Possibilities of AI-Generated Text Detection.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

WAVES: Benchmarking the Robustness of Image Watermarks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Explore Spurious Correlations at the Concept Level in Language Models for Text Classification.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
AutoDAN: Automatic and Interpretable Adversarial Attacks on Large Language Models.
CoRR, 2023

More Context, Less Distraction: Visual Classification by Inferring and Conditioning on Contextual Attributes.
CoRR, 2023

GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint.
CoRR, 2023

On the Possibilities of AI-Generated Text Detection.
CoRR, 2023

C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator.
Proceedings of the International Conference on Machine Learning, 2023

2022
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Transferring Fairness under Distribution Shifts via Fair Consistency Regularization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Understanding the Generalization Benefit of Model Invariance from a Data Perspective.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


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