:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Peiran, Wang, Haohan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2410.08665
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dist2ill: Distributional Distillation for One-Pass Uncertainty Estimation in Large Language Models
by: Zhao, Yicong, et al.
Published: (2025)

Dataset Distillation via the Wasserstein Metric
by: Liu, Haoyang, et al.
Published: (2023)

Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
by: Nie, Guangkun, et al.
Published: (2024)

Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models
by: Zhou, Andy, et al.
Published: (2023)

DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment
by: Wang, Hao, et al.
Published: (2025)

DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting
by: Liang, Daojun, et al.
Published: (2024)

IPD: Boosting Sequential Policy with Imaginary Planning Distillation in Offline Reinforcement Learning
by: Qin, Yihao, et al.
Published: (2026)

FairDD: Fair Dataset Distillation
by: Zhou, Qihang, et al.
Published: (2024)

DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agents
by: Wang, Taiyi, et al.
Published: (2024)

DistShap: Scalable GNN Explanations with Distributed Shapley Values
by: Akkas, Selahattin, et al.
Published: (2025)

RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
by: Yi, Hang, et al.
Published: (2026)

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

Curvature Dynamic Black-box Attack: revisiting adversarial robustness via dynamic curvature estimation
by: Sun, Peiran
Published: (2025)

GenoTEX: An LLM Agent Benchmark for Automated Gene Expression Data Analysis
by: Liu, Haoyang, et al.
Published: (2024)

LLM4DistReconfig: A Fine-tuned Large Language Model for Power Distribution Network Reconfiguration
by: Christou, Panayiotis, et al.
Published: (2025)

TrajFlow: Nation-wide Pseudo GPS Trajectory Generation with Flow Matching Models
by: Li, Peiran, et al.
Published: (2026)

Adaptive Consensus Gradients Aggregation for Scaled Distributed Training
by: Choukroun, Yoni, et al.
Published: (2024)

Efficient and Robust Knowledge Distillation from A Stronger Teacher Based on Correlation Matching
by: Niu, Wenqi, et al.
Published: (2024)

Conflict-Aware Adversarial Training
by: Xue, Zhiyu, et al.
Published: (2024)

Path-Guided Flow Matching for Dataset Distillation
by: Li, Xuhui, et al.
Published: (2026)

Distribution Matching for Self-Supervised Transfer Learning
by: Jiao, Yuling, et al.
Published: (2025)

PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models
by: Yu, Ye, et al.
Published: (2025)

ToxiGAN: Toxic Data Augmentation via LLM-Guided Directional Adversarial Generation
by: Li, Peiran, et al.
Published: (2026)

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

TextReg: Mitigating Prompt Distributional Overfitting via Regularized Text-Space Optimization
by: Fu, Lucheng, et al.
Published: (2026)

Real-Fake: Effective Training Data Synthesis Through Distribution Matching
by: Yuan, Jianhao, et al.
Published: (2023)

One-Step Diffusion Distillation through Score Implicit Matching
by: Luo, Weijian, et al.
Published: (2024)

Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data
by: Kong, Lingkai, et al.
Published: (2025)

SIPDO: Closed-Loop Prompt Optimization via Synthetic Data Feedback
by: Yu, Yaoning, et al.
Published: (2025)

Distillation of Large Language Models via Concrete Score Matching
by: Kim, Yeongmin, et al.
Published: (2025)

Domain Generalization via Pareto Optimal Gradient Matching
by: Do, Khoi, et al.
Published: (2025)

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis
by: Liu, Haoyang, et al.
Published: (2025)

zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning
by: Wang, Zhipeng, et al.
Published: (2023)

Integrating Distribution Matching into Semi-Supervised Contrastive Learning for Labeled and Unlabeled Data
by: Nakayama, Shogo, et al.
Published: (2026)

Minifinetuning: Low-Data Generation Domain Adaptation through Corrective Self-Distillation
by: Belcak, Peter, et al.
Published: (2025)

Stratos: An End-to-End Distillation Pipeline for Customized LLMs under Distributed Cloud Environments
by: Dai, Ziming, et al.
Published: (2025)

Posterior Mean Matching: Generative Modeling through Online Bayesian Inference
by: Salazar, Sebastian, et al.
Published: (2024)

Revisiting Gradient Staleness: Evaluating Distance Metrics for Asynchronous Federated Learning Aggregation
by: Wilhelm, Patrick, et al.
Published: (2026)

Aggregation Alignment for Federated Learning with Mixture-of-Experts under Data Heterogeneity
by: Fang, Zihan, et al.
Published: (2026)

Imitation Learning as Return Distribution Matching
by: Lazzati, Filippo, et al.
Published: (2025)