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Peter Tu

3 accepted papers

2026

All Roads Lead to Rome: Incentivizing Divergent Thinking in Vision-Language Models

CVPR 2026

Recent studies have demonstrated that Reinforcement Learning (RL), notably Group Relative Policy Optimization (GRPO), can intrinsically elicit and enhance the reasoning capabilities of Vision-Language Models (VLMs). However, despite the promise, the underlying mechanisms that drive the effectiveness

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2024

Adversarial Purification with the Manifold Hypothesis

AAAI 2024technical

In this work, we formulate a novel framework for adversarial robustness using the manifold hypothesis. This framework provides sufficient conditions for defending against adversarial examples. We develop an adversarial purification method with this framework. Our method combines manifold learning wi…

2024

IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models

ICLR 2024poster

We present a diffusion-based image morphing approach with perceptually-uniform sampling (IMPUS) that produces smooth, direct and realistic interpolations given an image pair. The embeddings of two images may lie on distinct conditioned distributions of a latent diffusion model, especially when they…