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Hengyuan Cao

8 accepted papers

2026

Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling

ICML 2026spotlight

The rapid evolution of generative models has unlocked new potentials in protein binder design, a pivotal task in structural biology, by facilitating end-to-end generation via joint sequence-structure modeling or hallucination. However, existing approaches are predominantly implemented under a single…

Cited by 0SourceScholar
2026

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models

CVPR 2026

Dataset distillation enables efficient training by distilling the information of large-scale datasets into significantly smaller synthetic datasets. Diffusion based paradigms have emerged in recent years, offering novel perspectives for dataset distillation. However, they typically necessitate addit

Cited by 0SourceScholar
2026

Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs

ICML 2026poster

Existing preference datasets for text-to-image (T2I) models typically store only the final winner/loser images. This representation is insufficient for rectified flow (RF) models, whose generation is naturally indexed by a specific prior noise sample and follows a nearly straight denoising trajector…

Cited by 0SourceScholar
2026

Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation

CVPR 2026

Efficient streaming video generation is critical for simulating interactive and dynamic worlds. Existing methods distill few-step video diffusion models with sliding window attention, using initial frames as sink tokens to maintain attention performance and reduce error accumulation. However, video

Cited by 0SourcecodeScholar
2025

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis

NeurIPS 2025poster

Video generative models can be regarded as world simulators due to their ability to capture dynamic, continuous changes inherent in real-world environments. These models integrate high-dimensional information across visual, temporal, spatial, and causal dimensions, enabling predictions of subjects i…

Cited by 0SourcecodeScholar
2025

InPO: Inversion Preference Optimization with Reparametrized DDIM for Efficient Diffusion Model Alignment

CVPR 2025highlight

Without using explicit reward, direct preference optimization (DPO) employs paired human preference data to fine-tune generative models, a method that has garnered considerable attention in large language models (LLMs). However, exploration of aligning text-to-image (T2I) diffusion models with human…

2025

OmniTry: Virtual Try-On Anything without Masks

NeurIPS 2025poster

Virtual Try-ON (VTON) is a practical and widely-applied task, for which most of existing works focus on clothes. This paper presents OmniTry, a unified framework that extends VTON beyond garment to encompass any wearable objects, e.g., jewelries and accessories, with mask-free setting for more pract…

Cited by 0SourcecodeScholar
2025

Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences

ICML 2025poster

Direct Preference Optimization (DPO) aligns text-to-image (T2I) generation models with human preferences using pairwise preference data. Although substantial resources are expended in collecting and labeling datasets, a critical aspect is often neglected: *preferences vary across individuals and sho…

Cited by 0SourcePDFScholar