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Xiaoyin Xu

7 accepted papers

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

Spherical Geometry Diffusion: Generating High-quality 3D Face Geometry via Sphere-anchored Representations

AAAI 2026technical

A fundamental challenge in text-to-3D face generation is achieving high-quality geometry. The core difficulty lies in the arbitrary and intricate distribution of vertices in 3D space, making it challenging for existing models to establish clean connectivity and resulting in suboptimal geometry. To a

Cited by 0SourcePDFScholar
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

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
2023

Volumetric Optimal Transportation by Fast Fourier Transform

ICLR 2023poster

The optimal transportation map finds the most economical way to transport one probability measure to another, and it has been applied in a broad range of applications in machine learning and computer vision. By the Brenier theory, computing the optimal transport map is equivalent to solving a Monge-…

Cited by 0SourcePDFScholar
2022

Efficient Optimal Transport Algorithm by Accelerated Gradient Descent

AAAI 2022technical

Optimal transport (OT) plays an essential role in various areas like machine learning and deep learning. However, computing discrete optimal transport plan for large scale problems with adequate accuracy and efficiency is still highly challenging. Recently, methods based on the Sinkhorn algorithm…

Cited by 20SourcePDFScholar
2021

Cortical Surface Shape Analysis Based on Alexandrov Polyhedra

ICCV 2021poster

Shape analysis has been playing an important role in early diagnosis and prognosis of neurodegenerative diseases such as Alzheimer's diseases (AD). However, obtaining effective shape representations remains challenging. This paper proposes to use the Alexandrov polyhedra as surface-based shape signa…

Cited by 0PDFScholar