:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Shi, Dingyuan, Zhang, Lulu, Tong, Yongxin, Xu, Ke
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2502.00725
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

eXpath: Explaining Knowledge Graph Link Prediction with Ontological Closed Path Rules
by: Sun, Ye, et al.
Published: (2024)

Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering
by: Niu, Yiming, et al.
Published: (2025)

Understanding and Mitigating Memorization in Diffusion Models for Tabular Data
by: Fang, Zhengyu, et al.
Published: (2024)

Preference Alignment for Diffusion Model via Explicit Denoised Distribution Estimation
by: Shi, Dingyuan, et al.
Published: (2024)

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach
by: Wei, Shuyue, et al.
Published: (2025)

Spatiotemporal Transformers for Predicting Avian Disease Risk from Migration Trajectories
by: Feng, Dingya, et al.
Published: (2025)

CAFEDistill: Learning Personalized and Dynamic Models through Federated Early-Exit Network Distillation
by: Liu, Boyi, et al.
Published: (2026)

Optimal Kernel Learning for Gaussian Process Models with High-Dimensional Input
by: Kang, Lulu, et al.
Published: (2025)

Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning
by: Shi, Yujun, et al.
Published: (2022)

Planner Aware Path Learning in Diffusion Language Models Training
by: Peng, Fred Zhangzhi, et al.
Published: (2025)

Understanding and Mitigating Overrefusal in LLMs from an Unveiling Perspective of Safety Decision Boundary
by: Pan, Licheng, et al.
Published: (2025)

PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting
by: Niu, Yiming, et al.
Published: (2025)

Improving the Euclidean Diffusion Generation of Manifold Data by Mitigating Score Function Singularity
by: Liu, Zichen, et al.
Published: (2025)

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
by: Zong, Yongshuo, et al.
Published: (2024)

Stochastic Shortest Path with Sparse Adversarial Costs
by: Johnson, Emmeran, et al.
Published: (2025)

DataSP: A Differential All-to-All Shortest Path Algorithm for Learning Costs and Predicting Paths with Context
by: Lahoud, Alan A., et al.
Published: (2024)

Path Planning for Masked Diffusion Model Sampling
by: Peng, Fred Zhangzhi, et al.
Published: (2025)

Understanding Diffusion Models by Feynman's Path Integral
by: Hirono, Yuji, et al.
Published: (2024)

Robust Clustering using Hyperdimensional Computing
by: Ge, Lulu, et al.
Published: (2023)

Empowering Diffusion Models on the Embedding Space for Text Generation
by: Gao, Zhujin, et al.
Published: (2022)

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces
by: Lyu, Yang, et al.
Published: (2025)

HOIST: Humanoid Optimization with Imitation and Sample-efficient Tuning for Manipulating Suspended Loads
by: Liu, Songyang, et al.
Published: (2026)

Test-time Adversarial Defense with Opposite Adversarial Path and High Attack Time Cost
by: Yeh, Cheng-Han, et al.
Published: (2024)

Data-Driven Adversarial Online Control for Unknown Linear Systems
by: Liu, Zishun, et al.
Published: (2023)

AIM: Attributing, Interpreting, Mitigating Data Unfairness
by: Liu, Zhining, et al.
Published: (2024)

Towards Practical Benchmarking of Data Cleaning Techniques: On Generating Authentic Errors via Large Language Models
by: Liu, Xinyuan, et al.
Published: (2025)

Modeling Inter-Intra Heterogeneity for Graph Federated Learning
by: Yu, Wentao, et al.
Published: (2024)

Proximal Diffusion Neural Sampler
by: Guo, Wei, et al.
Published: (2025)

R2IF: Aligning Reasoning with Decisions via Composite Rewards for Interpretable LLM Function Calling
by: Cheng, Aijia, et al.
Published: (2026)

TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
by: Shi, Juntong, et al.
Published: (2024)

Data-Driven Computing Methods for Nonlinear Physics Systems with Geometric Constraints
by: Tong, Yunjin
Published: (2024)

Could Large Language Models work as Post-hoc Explainability Tools in Credit Risk Models?
by: Geng, Wenxi, et al.
Published: (2026)

DataArc-SynData-Toolkit: A Unified Closed-Loop Framework for Multi-Path, Multimodal, and Multilingual Data Synthesis
by: Shi, Zhichao, et al.
Published: (2026)

Harmonic Path Integral Diffusion
by: Behjoo, Hamidreza, et al.
Published: (2024)

A Practical Diffusion Path for Sampling
by: Chehab, Omar, et al.
Published: (2024)

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks
by: Li, Miaomiao, et al.
Published: (2025)

Coarse-to-Fine Compositional Diffusion for Long-Horizon Planning
by: Park, Byoungwoo, et al.
Published: (2026)

Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling
by: Zhu, Dingyuan, et al.
Published: (2024)

Transition Path Sampling with Improved Off-Policy Training of Diffusion Path Samplers
by: Seong, Kiyoung, et al.
Published: (2024)

Divergent Paths: Separating Homophilic and Heterophilic Learning for Enhanced Graph-level Representations
by: Lei, Han, et al.
Published: (2025)