Distribution Matching

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9 papers in the last four weeks, against 1 the four weeks before. 0.1% of all new papers.

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Distribution Alignment for One-Shot Federated Learning via Optimal Transport
Jun 15, 2026Daniele Berardini, Vito Paolo Pastore, Vittorio MurinoDistribution Matching Optimal Transport
AI for Good · AI for Good (AIGO), Italian Institute of Technology, Genoa, Italy · MaLGa-DIBRIS, University of Genoa, Genoa, Italy +1
Cross-Modal Knowledge Distillation without Paired Data: Theoretical Foundation and Algorithm
Jun 9, 2026Trong Khiem Tran, Anh Duc Chu, Quang Hung Pham +2Cross-Modal Knowledge Distillation Cross-Modal Alignment
School of Electrical Engineering and Computer Science, Washington State University, Pullman, US · School of Information and Communications Technology, Hanoi University of Science and Technology, Hanoi, Vietnam
DistMatch: Adaptive Binning via Distribution Matching for Robust Sequential Conformal Prediction
May 30, 2026Enver Menadjiev, Jihyeon Seong, Jisu Yeo +1Distribution Shift Robustness Conformal Prediction
Korea Advanced Institute of Science and Technology, South Korea · INEEJI, South Korea
Generate in Reconstruction Space, Match in Semantic Space: Transport Geometry for One-Step Generation
May 30, 2026Hugues Van Assel, Edward De Brouwer, Saeed Saremi +2One-Step Generative Modeling Distribution Matching
Genentech
Sequential Neural Probabilistic Amplitude Shaping: Learning the Channel's Language
May 27, 2026Mohammad Taha Askari, Lutz Lampe, Amirhossein GhazisaeidiDistribution Matching Autoregressive Modeling
Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada · Nokia Bell Labs, 12 rue Jean Bart, 91300 Massy, France
LWM-CDE: A Representation Space for Wireless Data Reasoning and Transferability
May 22, 2026Sadjad Alikhani, Akshay Malhotra, Shahab Hamidi-Rad +1Contrastive Learning Representational Similarity Analysis
School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281 USA · InterDigital, Inc., USA
Multimodal Distribution Matching for Vision-Language Dataset Distillation
May 22, 2026Jongoh Jeong, Hoyong Kwon, Minseok Kim +1Cross-Modal Learning Cross-Modal Alignment
Visual Intelligence Lab., KAIST
Entropy Equivalence Testing
May 22, 2026Clément L. Canonne, Yash Pote, Jonathan Scarlett +1Distribution Matching
University of Sydney · National University of Singapore
The Value of Covariance Matching in Gaussian DDPMs and the Lanczos Sampler
May 21, 2026Md Sahil Akhtar, Aymane El Gadarri, Vivek F. Farias +1Diffusion Model Sampling Distribution Matching
Electrical Engineering and Computer Science · Massachusetts Institute of Technology · Operations Research Center +1
Distributional Alignment as a Criterion for Designing Task Vectors in In-Context Learning
May 20, 2026Jihoon Kwon, Jiwon Choi, Jy-yong SohnTask Vectors Distribution Matching
Seoul National University · Yonsei University
Marginal Alignment Does Not Guarantee Joint-Distribution Fidelity: An Official-Reference Audit of Nemotron-Personas-Korea with Cross-Locale Replication
May 15, 2026Joonhyung BaeDistribution Matching Synthetic Data Evaluation
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
Spectral Gradient Surgery for Domain-Generalizable Dataset Distillation
May 13, 2026Minyoung Oh, Najeong Chae, Jae-Young SimOOD Generalization Distribution Matching
Graduate School of Artificial Intelligence Ulsan National Institute of Science and Technology (UNIST) Ulsan, Republic of Korea
BSO: Safety Alignment Is Density Ratio Matching
May 12, 2026Tien-Phat Nguyen, Truong Nguyen, Thin Nguyen +3Functional Bregman Divergences Direct Preference Optimization
Hanoi University of Science and Technology Hanoi, Vietnam · Deakin University Burwood, VIC 3125, Australia · Max Planck Research School for Intelligent Systems +2
CAST: Collapse-Aware multi-Scale Topology Fusion for Multimodal Coreset Selection
May 12, 2026Boran Zhao, Hetian Liu, Zhenxian Hu +3Data Selection Distribution Matching
School of Software Engineering Xi’an Jiaotong University · the National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University
DeepLévy: Learning Heavy-Tailed Uncertainty in Highly Volatile Time Series
May 11, 2026Yang Yang, Du Yin, Hao Xue +1Time Series Forecasting Distribution Matching
University of New South Wales Australia NSW Sydney · The Hong Kong University of Science and Technology (Guangzhou)
Inverse Design for Conditional Distribution Matching
May 10, 2026Ori Meidler, Shaul Tolkovsky, Or ZukDiffusion Model Guidance Distribution Matching
Department of Statistics and Data Science Hebrew University of Jerusalem
Mutual Information Optimal Density Control of Linear Systems and Generalized Schrödinger Bridges with Reference Refinement
May 10, 2026Shoju Enami, Kenji KashimaStochastic Optimal Control Schrödinger Bridges
Graduate School of Informatics, Kyoto University, Kyoto, Japan
Learning Minimal-Deviation Corrections for Multi-Dimensional Mismodelling in HEP Simulations
May 8, 2026Matthias Schott, Lucie FlekDistribution Matching High-Energy Physics
Institute of Physics, University of Bonn, Germany · Bonn-Aachen International Center for Information Technology (b-it), University of Bonn, Germany
Q-MMR: Off-Policy Evaluation via Recursive Reweighting and Moment Matching
May 7, 2026Xiang Li, Nan JiangOff-Policy Evaluation Value Function Estimation
Nanjing University · UIUC
On Computing Total Variation Distance Between Mixtures of Product Distributions
May 5, 2026Weiming Feng, Yucheng Fu, Minji Yang +1Distribution Matching Approximation Algorithms
School of Computing and Data Science, The University of Hong Kong. · The Institute for Interdisciplinary Information Sciences, Tsinghua University.
Understanding Self-Supervised Learning via Latent Distribution Matching
May 5, 2026Fabian A Mikulasch, Friedemann ZenkeRepresentation Learning Self-Supervised Learning
Friedrich Miescher Institute for Biomedical Research, 4056 Basel, Switzerland · Faculty of Science, University of Basel, 4033 Basel, Switzerland
SemiGDA: Generative Dual-distribution Alignment for Semi-Supervised Medical Image Segmentation
Apr 25, 2026Kaiwen Huang, Yi Zhou, Yizhe Zhang +2Distribution Matching Semi-Supervised Medical Image Segmentation
Nanjing University of Science and Technology, Nanjing, China · Southeast University, Nanjing, China
Unsupervised Behavioral Compression: Learning Low-Dimensional Policy Manifolds through State-Occupancy Matching
Mar 27, 2026Andrea Fraschini, Davide Tenedini, Riccardo Zamboni +2RL Control Distribution Matching
Politecnico di Milano · Technion
Convergence Rates for Distribution Matching with Sliced Optimal Transport
Feb 11, 2026Gauthier Thurin, Claire Boyer, Kimia NadjahiDistribution Matching Sliced Wasserstein Distance
ENS-PSL · CNRS, ENS Paris, France · LMO, IUF, CELESTE +2
Factorizable joint shift revisited
Jan 21, 2026Dirk TascheDistribution Shift Robustness Label Shift
Centre for Business Mathematics and Informatics, North-West University, South Africa
Predicting Effects, Missing Distributions: Evaluating LLMs as Human Behavior Simulators in Operations Management
Sep 30, 2025Runze Zhang, Xiaowei Zhang, Mingyang ZhaoLLM Evaluation Human Behavior Simulation
Department of Industrial Engineering and Decision Analytics, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
A Discrepancy-Based Perspective on Dataset Condensation
Sep 12, 2025Tong Chen, Raghavendra SelvanDistribution Matching Dataset Distillation
Department of Computer Science, University of Copenhagen, Denmark
Efficient and Stable Multi-Dimensional Kolmogorov-Smirnov Distance
Apr 15, 2025Peter Matthew Jacobs, Foad Namjoo, Jeff M. PhillipsTwo-Sample Testing Distribution Matching
University of Wisconsin–Madison, USA · University of Utah, USA
Bringing Generative Learning to Representation Learning: Self-Supervised Transfer Learning as Distribution Matching
Feb 20, 2025Yuling Jiao, Wensen Ma, Defeng Sun +2Visual Representation Learning Distribution Matching
School of Artificial Intelligence, Wuhan University, 430072, Wuhan, China · School of Mathematics and Statistics, Wuhan University, Wuhan, 430072, China · Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China +2
Accuracy is Not Enough: A Divergence-Based Approach to Evaluate Fidelity Loss in Quantized LLMs
Date pendingShahzeb Qamar, Lorenz Sparrenberg, Christian Bauckhage +5LLM Quantization LLM Evaluation
Fraunhofer IAIS, Germany · PhenoRob Cluster of Excellence, University of Bonn, Germany · Lamarr Institute for Machine Learning and Artificial Intelligence, Germany +4

Jun 15, 2026, cs.LGJ/K move · Enter open · S save

Distribution Alignment for One-Shot Federated Learning via Optimal Transport

Daniele Berardini, Vito Paolo Pastore, Vittorio Murino

AI for Good · AI for Good (AIGO), Italian Institute of Technology, Genoa, Italy · MaLGa-DIBRIS, University of Genoa, Genoa, Italy+1

Distribution Matching Optimal Transport Federated Learning Heterogeneous Federated Learning

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One-Shot Federated Learning (OSFL) addresses extreme communication regimes in which clients interact with the server only once, amplifying the impact of heterogeneous client data distributions. In particular, the interaction of domain shift and label shift across clients induces misaligned feature representations that cannot be corrected through iterative optimization. Existing OSFL methods rely on distillation, server-side generation or ensemble-based aggregation, but assume aligned representations or address domain and label shift separately. We introduce SLOT-Align (Single-round, Learning-free Optimal Transport Alignment), a geometry-aware feature harmonization framework for OSFL. SLOT-Align uses a shared frozen encoder to extract compact feature statistics, constructs a global reference via Bures-Wasserstein barycenters, and aligns local representations using closed-form geodesic optimal transport maps. The method is computationally efficient and can be combined with existing OSFL pipelines relying on frozen encoders without modifying their training procedures. Extensive experiments across multiple benchmarks, pretrained backbones, and OSFL methods show that SLOT-Align consistently improves accuracy and robustness under joint domain and label shift.

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