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14 papers in the last four weeks, down 18% on the four weeks before. 0.2% of all new papers.

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InfoQuant: Shaping Activation Distributions for Low-Bit LLM Quantization
May 25, 2026Ke Li, Dong An, Xiaoling Zang +6Large Language Model Quantization Distributions
School of Software Technology, Zhejiang University · Ant Group · College of Computer Science and Technology, Zhejiang University of Technology +3
Estimating Mixture Distributions via Stochastic Mirror Descent
May 24, 2026Mohammadreza Ahmadypour, Tara Javidi, Farinaz KoushanfarMixture Models Bregman Divergences
Department of Electrical and Computer Engineering University of California San Diego, San Diego, CA, USA
CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection
May 23, 2026Zexi Jia, Zhiqiang Yuan, Xiaoyue Duan +3Ai-Generated Image Detection Fake News
Tencent WeChat AI, Beijing, China · Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
Detecting Metastable Basins in High Dimensions via Marginal Trajectory Distribution Discrimination
May 22, 2026Taj Jones-McCormickMetastable Samples Basin
Riemannian Archetypal Analysis: Interpretable non-linear data analysis on deformed star distributions
May 22, 2026Willem Diepeveen, Deanna NeedellRiemannian Manifolds Nonlinearity
Department of Mathematics University of California, Los Angeles Los Angeles, CA 90095, USA
Geometry-Adaptive Explainer for Faithful Dictionary-Based Interpretability under Distribution Shift
May 21, 2026Sungjun Lim, Heedong Kim, Andrew Lee +1Interpretability Mechanistic Interpretability
aYonsei University · bHarvard University
Symbolic Density Estimation for Discrete Distributions
May 20, 2026Ziwen Liu, Meng LiDensity Ratio Estimation Distributions
Rice University Houston, TX
Automated ICD Classification of Psychiatric Diagnoses: From Classical NLP to Large Language Models
May 20, 2026Fernando Ortega, Raúl Lara-Cabrera, Jorge Dueñas-Lerín +3International Classification Of Disease Coding Mental Health
Department of Sistemas Informáticos, Universidad Politécnica de Madrid, Spain · KNODIS Research Group, Universidad Politécnica de Madrid, Spain · CIBERSAM ISCIII, Spain +8
A Unified Framework for Uncertainty-Aware Explainable Artificial Intelligence: A Case Study in Power Quality Disturbance Classification
May 20, 2026Yinsong Chen, Samson S. Yu, Zhong Li +1Uncertainty-Aware Classification Bayesian Neural Networks
School of Engineering, Deakin University, Melbourne, 3216, VIC, Australia · Faculty of Mathematics and Computer Science, FernUniversität in Hagen, 58084, Germany · Department of Computing Technologies, Swinburne University of Technology, Hawthorn, 3122, VIC, Australia
Same Target, Different Basins: Hard vs. Soft Labels for Annotator Distributions
May 20, 2026Mirerfan Gheibi, Gashin GhazizadehLabel Propagation Human Annotators
Independent Researcher.
Density-Ratio Losses for Post-Hoc Learning to Defer
May 19, 2026Alexander Soen, Ragnar Thobaben, Joakim Jaldén +1Post-Hoc Loss Function
KTH⋄ · Google Research†
Beyond Mode Collapse: Distribution Matching for Diverse Reasoning
May 19, 2026Xiaozhe Li, Yang Li, Xinyu Fang +10Kullback-Leibler Divergence Collapse
1Tongji University, China · 6Independent · 2Shanghai AI Laboratory, China +3
Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models
May 18, 2026Abdelhakim Ziani, Andras Horvath, Paolo BallariniLong-Tailed Distribution Generative Models
Université Paris Saclay, Lab. MICS, CentraleSupélec, Gif-sur-Yvette, France · Università di Torino, Torino, Italy
On Stability and Decomposition of Sample Quantiles under Heavy-Tailed Distributions
May 18, 2026Choudur LakshminarayanQuantile Regression Long-Tailed Distribution
School of Business, Stevens Institute of Technology
Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling
May 18, 2026Ziwei Wang, Jing Chen, Ruichao Liang +6Large Language Model Jailbreaks Jailbreak Attacks
Wuhan University · Nanyang Technological University · Southeast University +1
BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation
May 17, 2026Yuhan Xie, Chen Lyu, Jingrong HuangFederated Learning Balanced Learning
Shanghai University of Finance and Economics, China · MoE Key Laboratory of Interdisciplinary Research of Computation and Economics, China.
A Distribution Matching Approach to Neural Piano Transcription with Optimal Transport
May 17, 2026Weixing Wei, Raynaldi Lalang, Dichucheng Li +1Multi-Instrument Music Transcription Transfer Learning
Graduate School of Informatics, Kyoto University, Japan · Graduate School of Engineering, Kyoto University, Japan · Independent Researcher, Hong Kong, China
Statistical Unlearning of Distributions: A Hypothesis Testing Approach
May 15, 2026Aaradhya Pandey, Sanjeev KulkarniExact Unlearning Distributions
Princeton University
BARRIER: Bounded Activation Regions for Robust Information Erasure
May 15, 2026Jan Miksa, Patryk Krukowski, Przemysław Spurek +2Exact Unlearning Concept Erasure
Jagiellonian University IDEAS Research Institute · Jagiellonian University NASK - National Research Institute
SID: Sliding into Distribution for Robust Few-Demonstration Manipulation
May 13, 2026Yicheng Ma, Wei Yu, Zhian Su +2Robotic Manipulation Policies Egocentric Vision
1Grasp Lab, Zhejiang University · 2Torch Kernel Co., Ltd.
Drag within Prior Distribution: Text-Conditioned Point-Based Image Editing within Distribution Constraints
May 13, 2026Haoyang Hu, Masataka Seo, Yen-Wei ChenDiffusion-Based Image Editing Image Editing
† Ritsumeikan University, Graduate School of Information and Engineering · ⋆Osaka Institute of Technology
Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics
May 12, 2026Boming Liu, Jin Dong, Jamie LianPower Systems Distributions
Electrification and Energy Infrastructures Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830 USA
Differentially Private Sampling from Distributions via Wasserstein Projection
May 11, 2026Shokichi Takakura, Seng Pei Liew, Satoshi HasegawaWasserstein Distance Distributions
LY Corporation
GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction
May 11, 2026Urchade Zaratiana, Ash Lewis, George Hurn-MaloneyNamed-Entity Recognition Machine-Generated Text Detection
Fastino Labs
Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions
May 11, 2026Tsuyoshi OkitaCausal Discovery Methods Causal
Kyushu Institute of Technology
Inverse Design for Conditional Distribution Matching
May 10, 2026Ori Meidler, Shaul Tolkovsky, Or ZukText-Conditioned Diffusion Model Generative Models
Department of Statistics and Data Science Hebrew University of Jerusalem
Learning Large-Scale Modular Addition with an Auxiliary Modulus
May 8, 2026Hanato Kikuchi, Ryosuke Masuya, Kazuhiko Kawamoto +1Modular Framework Covariate Shift
Chiba University · National Institute of Informatics
Inference-Time Attribute Distribution Alignment for Unconditional Diffusion
May 8, 2026Hao Luan, See-Kiong Ng, Chun Kai LingDiffusion Alignment Diffusion Models
School of Computing, National University of Singapore · Institute of Data Science, National University of Singapore
On the Robustness of Distribution Support under Diffusion Guidance
May 8, 2026Ruijia Cao, Yuchen Wu, Nisha ChandramoorthyGenerative Processes Distributions
Center for Applied Mathematics, Cornell University · School of Operations Research and Information Engineering, Cornell University · Department of Statistics, The University of Chicago
Path-Coupled Bellman Flows for Distributional Reinforcement Learning
May 7, 2026Boyang Xu, Qing Zou, Siqin Yang +1Distributional Reinforcement Learning Bellman Equation
School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA.
Christoffel-DPS: Optimal sensor placement in diffusion posterior sampling for arbitrary distributions
May 7, 2026James Rowbottom, Nick Huang, Carola-Bibiane Schönlieb +1Optimal Sensor Placement Posterior Sampling
Department of Mathematics Simon Fraser University Canada
Estimate Level Adjustment For Inference With Proxies Under Random Distribution Shifts
May 7, 2026Steven Wilkins-Reeves, Alexandra N. M. Darmon, Deeksha SinhaCovariate Shift Causal Inferences
Central Applied Science, Meta · New York, NY, USA · Menlo Park, CA, USA
Continuous-Time Distribution Matching for Few-Step Diffusion Distillation
May 7, 2026Tao Liu, Hao Yan, Mengting Chen +8Diffusion Models Distribution Matching Distillation
1VCIP, College of Computer Science, Nankai University · 2Alibaba Group · College of Artificial Intelligence, Jilin University
Whole-body CT attenuation and volume charts from routine clinical scans via evidence-grounded LLM report filtering
May 7, 2026Christian Wachinger, Bernhard Renger, Christopher Späth +2Cone-Beam Computed Tomography Report
Institute of Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany · Munich Data Science Institute (MDSI), Technical University of Munich, Munich, Germany · Munich Center for Machine Learning (MCML), Munich, Germany +1
A geometric relation of the error introduced by sampling a language model's output distribution to its internal state
May 6, 2026Albert F. ModenbachSingle-Token Output Distributions Chess
Department of Mathematics, King’s College London, United Kingdom.
Power Distribution Bridges Sampling, Self-Reward RL, and Self-Distillation
May 6, 2026Akiyoshi Tomihari, Issei SatoUnsupervised On-Policy Self-Distillation Large Language Model Reinforcement Learning
Department of Computer Science, The University of Tokyo
When Prompts Interact: Assessing Prompt Arithmetic for Deconfounding under Distribution Shift
May 4, 2026Zhecheng Sheng, Yongsen Tan, Xiruo Ding +2Soft Prompt Tuning Distribution Shifts
University of Minnesota · University of Washington · 3Stanford University
Measuring Differences between Conditional Distributions using Kernel Embeddings
May 4, 2026Peter Moskvichev, Siu Lun Chau, Dino SejdinovicConditional Distribution Maximum Mean Discrepancy
School of Mathematical Sciences, Adelaide University · College of Computing and Data Science, Nanyang Technological University
Fairness for distribution network operations and planning
Apr 30, 2026Pedro F. C. de Carvalho, Zijie Liu, Md Umar Hashmi +1Algorithmic Fairness Bringing Network Coding
KU Leuven, division Electa in Leuven · & EnergyVille in Genk, Belgium
Student Classroom Behavior Recognition Based on Improved YOLOv8s
Apr 30, 2026Xiang Gao, Shuai HangYolo26 Open-Vocabulary Action Recognition
School of Physics and Information Technology Shaanxi Normal University Xi’an, 710062, China
Sample Selection Using Multi-Task Autoencoders in Federated Learning with Non-IID Data
Apr 28, 2026Emre Ardıç, Yakup GençFederated Learning Support Vector Machines
Gebze Technical University, Department of Computer Engineering, Gebze, Kocaeli 41400, Turkey
Pliable rejection sampling
Apr 24, 2026Akram Erraqabi, Michal Valko, Alexandra Carpentier +1Rejection Sampling Rejection
MILA, Universit´e de Montr´eal, Montr´eal, QC H3C 3J7, Canada · INRIA Lille - Nord Europe, SequeL team, 40 avenue Halley 59650, Villeneuve d’Ascq, France · Institut für Mathematik, Univertät Potsdam, Germany, Haus 9 Karl-Liebknecht-Strasse 24-25, D-14476 Potsdam +1
Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations
Apr 22, 2026Bowen Zuo, Dongruo Zhou, Yinglun ZhuTest Time Inference-Time
University of California, Riverside · 2Indiana University Bloomington
Robust Out-of-Distribution Stochastic Optimization
Apr 22, 2026Xianyu Li, Huan Xu, Xiaolin Huang +1Distributionally-Robust Optimization Out-Of-Distribution
Department of Automation, Tsinghua University · Antai College of Economics & Management, Shanghai Jiao Tong University · Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University
A Network-Aware Evaluation of Distributed Energy Resource Control in Smart Distribution Systems
Apr 21, 2026Houchao GanDistributed Energy Resources Distributions
Department of Computer Science City University of New York
Beyond One Output: Visualizing and Comparing Distributions of Language Model Generations
Apr 20, 2026Emily Reif, Claire Yang, Jared Hwang +3Large Language Model Generation Distributional Information
University of Washington, Seattle, WA, USA · Allen Institute for AI
Distributional Off-Policy Evaluation with Deep Quantile Process Regression
Apr 20, 2026Qi Kuang, Chao Wang, Yuling Jiao +1Distributional Reinforcement Learning Off-Policy Learning
School of Statistics and Data Science, and Philosophy and Social Sciences Laboratory of Data Science in Finance and Economics at the Ministry of Education,2026 Jiangxi University of Finance and Economics · School of Statistics and Data Science, Shanghai University of Finance and EconomicsApr · School of Artificial Intelligence, and Hubei Key Laboratory of Computational Science, 24 Wuhan University
BIASEDTALES-ML: A Multilingual Dataset for Analyzing Narrative Attribute Distributions in LLM-Generated Stories
Apr 18, 2026Yuxuan Ouyang, yingfeng luo, JingBo Zhu +1Narrative Generation Narratives
School of Computer Science and Engineering, Northeastern University, Shenyang, China · NiuTrans Research, Shenyang, China
A Community-Based Approach for Stance Distribution and Argument Organization
Apr 18, 2026Rudra Ranajee Saha, Laks V. S. Lakshmanan, Raymond T. NgArgumentation Frameworks Political Discourse
University of British Columbia
Beyond Distribution Sharpening: The Importance of Task Rewards
Apr 17, 2026Sarthak Mittal, Leo Gagnon, Guillaume LajoieDistributional Reinforcement Learning Sharpness-Aware Minimization
1Mila · 2Universit´e de Montr´eal
PRIM-cipal components analysis
Apr 16, 2026Tianhao Liu, Daniel Andrés Díaz-Pachón, J. Sunil RaoPrincipal Component Analysis Unsupervised
Division of Biostatistics, University of Miami, Miami, FL, 33136 USA · University of Minnesota, Minneapolis, MN, 55414 USA
From Order to Distribution: An Exact Operator Framework for Forgetting in Continual Learning
Apr 15, 2026Zonghuan Xu, Xingjun MaContinual Learning Learning-Augmented Algorithms
Institute of Trustworthy Embodied AI, Fudan University, Shanghai, China · Shanghai Key Laboratory of Multimodal Embodied AI, Shanghai, China
Synthesizing real-world distributions from high-dimensional Gaussian Noise with Fully Connected Neural Network
Apr 10, 2026Joanna KomorniczakSynthetic Tabular Data Synthetic Data
Department of Systems and Computer Networks, Wrocław University of Science and Technology
Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation
Apr 3, 2026Xingtong Ge, Yi Zhang, Yushi Huang +6Autoregressive Video Generation Video Generation
Hong Kong University of Science and Technology · Vivix Group Limited
Learning to Recorrupt: Noise Distribution Agnostic Self-Supervised Image Denoising
Mar 26, 2026Brayan Monroy, Jorge Bacca, Julián TachellaNoise-Aware Iterative Denoising Methods
Universidad Industrial de Santander, Colombia · CNRS, ENS de Lyon, France
Trustworthy Predictive Distributions for Tail Events with Semiparametric Diagnostic Transport Maps
Mar 11, 2026Elizabeth Cucuzzella, Rafael Izbicki, Ann B. LeeProbabilistic Forecasting Tropical Cyclones
Department of Statistics and Data Science, Carnegie Mellon University · Department of Statistics, Federal University of Sao Carlos
From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning
Mar 10, 2026Zhanyi Sun, Shuran SongDistributional Reinforcement Learning Robot Policies
1Stanford University.
Cross-Resolution Distribution Matching for Diffusion Distillation
Mar 6, 2026Feiyang Chen, Hongpeng Pan, Haonan Xu +3Visual Fidelity Distributions
Huawei, Shanghai & Hangzhou, China · Nanjing University of Science and Technology, Nanjing, China
Convergence Rates for Distribution Matching with Sliced Optimal Transport
Feb 11, 2026Gauthier Thurin, Claire Boyer, Kimia NadjahiOptimal Transport Approach Wasserstein Distance
ENS-PSL · CNRS, ENS Paris, France · LMO, IUF, CELESTE +2
Manifold-Aware Perturbations for Constrained Generative Modeling
Jan 30, 2026Katherine Keegan, Lars RuthottoGenerative Models Manifold Perspective
Department of Mathematics, Emory University, Atlanta, Georgia, USA.

May 25, 2026, cs.LGJ/K move · Enter open · S save

InfoQuant: Shaping Activation Distributions for Low-Bit LLM Quantization

Ke Li, Dong An, Xiaoling Zang, Can Ye+5

School of Software Technology, Zhejiang University · Ant Group · College of Computer Science and Technology, Zhejiang University of Technology+3

Large Language Model Quantization Distributions Outliers

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Low-bit activation quantization remains a major bottleneck in efficient large language model (LLM) deployment. The difficulty is not only that activations contain outliers, but that their distributions are often poorly matched to a low-bit uniform quantizer. Existing post-training quantization (PTQ) methods suppress peaks, balance channels, or minimize reconstruction error, yet they rarely specify what activation distribution is actually easy to discretize. As a result, activations may appear numerically smoother while still incurring large quantization error because the quantization range remains wide or most values collapse into a few levels near the mean. We recast activation transformation as quantizer-facing distribution design and analyze quantization error from an information-theoretic perspective. Our analysis shows that quantization-friendly activations should jointly have a smaller numerical range and sufficient dispersion within that range. Guided by this analysis, we propose InfoQuant, a train-free method that employs Peak Suppression Orthogonal Transformation (PSOT) to shape activations into more quantization-friendly distributions. We further introduce adaptive outlier-token selection to improve the robustness of PSOT during optimization. Across multiple LLM families, InfoQuant consistently outperforms prior PTQ and end-to-end training baselines. Under W4A4KV4, it preserves 97% of floating-point accuracy on average and reduces the LLaMA-2 13B performance gap by 42% over the previous state of the art. Code is available at https://github.com/LLIKKE/InfoQuant

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