5 papers
Unlearning Offline Stochastic Multi-Armed Bandits
Zichun Ye, Runqi Wang, Xuchuang Wang +3
Machine unlearning aims to unlearn data points from a learned model, offering a principled way to process data-deletion requests and mitigate privacy risks without full retraining.…
ARC Is a Vision Problem!
Keya Hu, Ali Cy, Linlu Qiu +5
The Abstraction and Reasoning Corpus (ARC) is designed to promote research on abstract reasoning, a fundamental aspect of human intelligence. Common approaches to ARC treat it as a…
Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models
Runqian Wang, Yilun Du
We introduce Equilibrium Matching (EqM), a generative modeling framework built from an equilibrium dynamics perspective. EqM discards the non-equilibrium, time-conditional dynamics…
Diffuse and Disperse: Image Generation with Representation Regularization
Runqian Wang, Kaiming He
The development of diffusion-based generative models over the past decade has largely proceeded independently of progress in representation learning. These diffusion models typical…
VLMInferSlow: Evaluating the Efficiency Robustness of Large Vision-Language Models as a Service
Xiasi Wang, Tianliang Yao, Simin Chen +5
Vision-Language Models (VLMs) have demonstrated great potential in real-world applications. While existing research primarily focuses on improving their accuracy, the efficiency re…