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20182024
most citedImproving Adversarial Robustness via Promoting Ensemble Diversity

190 citations · 210 across the 12 of their papers we have counts for

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16 papers · 1 filter

cs.LG20243 cited

Improved Techniques for Optimization-Based Jailbreaking on Large Language Models

Xiaojun Jia, Tianyu Pang, Chao Du +5

Large language models (LLMs) are being rapidly developed, and a key component of their widespread deployment is their safety-related alignment. Many red-teaming efforts aim to jail…

cs.LG2024

Graph Diffusion Policy Optimization

Yijing Liu, Chao Du, Tianyu Pang +3

Recent research has made significant progress in optimizing diffusion models for downstream objectives, which is an important pursuit in fields such as graph generation for drug de…

cs.LG2024

Benchmarking Large Multimodal Models against Common Corruptions

Jiawei Zhang, Tianyu Pang, Chao Du +3

This technical report aims to fill a deficiency in the assessment of large multimodal models (LMMs) by specifically examining the self-consistency of their outputs when subjected t…

cs.LG2024

Locality Sensitive Sparse Encoding for Learning World Models Online

Zichen Liu, Chao Du, Wee Sun Lee +1

Acquiring an accurate world model online for model-based reinforcement learning (MBRL) is challenging due to data nonstationarity, which typically causes catastrophic forgetting fo…

cs.LG20231 cited

Gaussian Mixture Solvers for Diffusion Models

Hanzhong Guo, Cheng Lu, Fan Bao +4

Recently, diffusion models have achieved great success in generative tasks. Sampling from diffusion models is equivalent to solving the reverse diffusion stochastic differential eq…

cs.LG2023

Finetuning Text-to-Image Diffusion Models for Fairness

Xudong Shen, Chao Du, Tianyu Pang +3

The rapid adoption of text-to-image diffusion models in society underscores an urgent need to address their biases. Without interventions, these biases could propagate a skewed wor…