Cover Image

Path-Guided Flow Matching for Dataset Distillation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Xuhui, Luo, Zhengquan, Liu, Xiwei, Yu, Yongqiang, Xu, Zhiqiang
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GeoDM: Geometry-aware Distribution Matching for Dataset Distillation
by: Li, Xuhui, et al.
Published: (2025)

Local-Curvature-Aware Knowledge Graph Embedding: An Extended Ricci Flow Approach
by: Luo, Zhengquan, et al.
Published: (2025)

Utility Boundary of Dataset Distillation: Scaling and Configuration-Coverage Laws
by: Luo, Zhengquan, et al.
Published: (2025)

Flow Matching with Arbitrary Auxiliary Paths
by: Peng, Xin, et al.
Published: (2026)

Bridging the Last Mile of Prediction: Enhancing Time Series Forecasting with Conditional Guided Flow Matching
by: Xu, Huibo, et al.
Published: (2025)

Energy Guided Geometric Flow Matching
by: Zweig, Aaron, et al.
Published: (2025)

EnfoPath: Energy-Informed Analysis of Generative Trajectories in Flow Matching
by: Li, Ziyun, et al.
Published: (2025)

Training Free Guided Flow Matching with Optimal Control
by: Wang, Luran, et al.
Published: (2024)

Boosting Maximum Entropy Reinforcement Learning via One-Step Flow Matching
by: Li, Zeqiao, et al.
Published: (2026)

Class-Imbalanced-Aware Adaptive Dataset Distillation for Scalable Pretrained Model on Credit Scoring
by: Li, Xia, et al.
Published: (2025)

Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective
by: Shaul, Neta, et al.
Published: (2024)

FlowDistill: Scalable Traffic Flow Prediction via Distillation from LLMs
by: Yu, Chenyang, et al.
Published: (2025)

Distilling Two-Timed Flow Models by Separately Matching Initial and Terminal Velocities
by: Khungurn, Pramook, et al.
Published: (2025)

PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation
by: Zhang, Junru, et al.
Published: (2026)

Score Distillation of Flow Matching Models
by: Zhou, Mingyuan, et al.
Published: (2025)

Epigraph-Guided Flow Matching for Safe and Performant Offline Reinforcement Learning
by: Tayal, Manan, et al.
Published: (2026)

GSTAM: Efficient Graph Distillation with Structural Attention-Matching
by: Rasti-Meymandi, Arash, et al.
Published: (2024)

Dataset Distillation for Offline Reinforcement Learning
by: Light, Jonathan, et al.
Published: (2024)

Dataset Distillation via Curriculum Data Synthesis in Large Data Era
by: Yin, Zeyuan, et al.
Published: (2023)

Towards Mitigating Architecture Overfitting on Distilled Datasets
by: Zhong, Xuyang, et al.
Published: (2023)

Prioritize Alignment in Dataset Distillation
by: Li, Zekai, et al.
Published: (2024)

Sharpen Your Flow: Sharpness-Aware Sampling for Flow Matching
by: Gupta, Aditi, et al.
Published: (2026)

LGCC: Enhancing Flow Matching Based Text-Guided Image Editing with Local Gaussian Coupling and Context Consistency
by: Liu, Fangbing, et al.
Published: (2025)

LAMP: Learnable Meta-Path Guided Adversarial Contrastive Learning for Heterogeneous Graphs
by: Li, Siqing, et al.
Published: (2024)

Flow Matching Meets Biology and Life Science: A Survey
by: Li, Zihao, et al.
Published: (2025)

Preference-Based Self-Distillation: Beyond KL Matching via Reward Regularization
by: Yu, Xin, et al.
Published: (2026)

Grounding and Enhancing Informativeness and Utility in Dataset Distillation
by: Wang, Shaobo, et al.
Published: (2026)

Enhancing Reasoning Capabilities in SLMs with Reward Guided Dataset Distillation
by: Padarha, Shreyansh
Published: (2025)

Drift Flow Matching
by: Ma, Chenrui, et al.
Published: (2026)

REMEDI: Relative Feature Enhanced Meta-Learning with Distillation for Imbalanced Prediction
by: Liu, Fei, et al.
Published: (2025)

Discrete Flow Matching
by: Gat, Itai, et al.
Published: (2024)

DeLo: Dual Decomposed Low-Rank Experts Collaboration for Continual Missing Modality Learning
by: Liu, Xiwei, et al.
Published: (2026)

Task-Specific Generative Dataset Distillation with Difficulty-Guided Sampling
by: Li, Mingzhuo, et al.
Published: (2025)

Edit Flows: Flow Matching with Edit Operations
by: Havasi, Marton, et al.
Published: (2025)

A Kinetic Energy Perspective of Flow Matching
by: Li, Ziyun, et al.
Published: (2026)

scDD: Latent Codes Based scRNA-seq Dataset Distillation with Foundation Model Knowledge
by: Yu, Zhen, et al.
Published: (2025)

GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models
by: Tang, Xiaohang, et al.
Published: (2026)

Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation
by: Monsefi, Amin Karimi, et al.
Published: (2026)

Flow Matching on General Geometries
by: Chen, Ricky T. Q., et al.
Published: (2023)

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning
by: Liu, Zeyuan, et al.
Published: (2025)