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5 papers in the last four weeks, up 67% on the four weeks before. 0.0% of all new papers.

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Latest papers 32

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Client and Training Data Selection for Computationally Efficient Synchronized Federated Learning
Sep 30, 2026Muzaffer Citir, Hiroki Nishikawa, Sangyoung ParkFederated Learning Training Data
Smart Mobility Systems, Technical University of Berlin, Germany · Graduate School of Information Science and Technology, The University of Osaka, Japan
Screen Before You Serve: Simulation for Production Customer Experience AI Agents at 140M Scale
Sep 24, 2026Edesio Alcoba, Kevin Rossell, Aman Gupta +13User Simulation Clients
Nubank · Guardrails AI
Concurrent Split Learning Through Stable Client Clustering
Sep 24, 2026Mohammad Kohankhaki, Valentin Rentschler, Anke SchmeinkClients Fundamental Limits
Chair of Information Theory and Data Analytics, RWTH Aachen University, Aachen, Germany
Persuaded, Not Informed: Incentive-Misaligned Witnesses Defeat In-Context Grounding
Sep 23, 2026Rahul BalakaviPersuasion Elicitation
AmpUp Research
HybridFLow: SDN-Orchestrated Client Partitioning for Hybrid Federated Learning
Sep 9, 2026Osama Abu Hamdan, Rabin Pandey, Hao Che +2Federated Learning Fedavg
University of Texas at Arlington · Missouri University of Science and Technology · Meta Platforms, Inc.
PatientAct: Theory-Grounded Mental Health Client Simulation
Aug 13, 2026Sahand Sabour, TszYam NG, Yaqian Chen +3Simulated Patients User Simulation
The CoAI Group, DCST, Institute for Artificial Intelligence, Tsinghua University, Beijing, China · Department of Psychology, Beijing Normal University, Beijing, China · Counseling and Psychological Development Guidance Center, Tsinghua University, Beijing, China
Certifying What Helps Customer-Return Timing: A Screen-and-Confirm Test for Conditioning Signals, and Why Decay Is Nearly Enough
Aug 12, 2026Sang Su Lee, Vineeth Loganathan, Shishir Dash +1Time-To-Event Data Determinantal Point Process
Thumbtack, Inc. San Francisco, CA, USA
Context Is Not Authority: Structured Runtime Governance for Financial Market Agents
Aug 10, 2026Rui Tang, Qiangqiang Liu, Yichi Zhang +3Authority Banking
OpenAsk · Binance · New York University New York, New York, USA +2
Federated Foundation Models Fine-Tuning with Heterogeneous Compressed Clients
Jul 31, 2026Shengkun Zhu, Jinshan Zeng, Zhihua Allen-Zhao +5Fedavg Parameter-Efficient Fine-Tuning Methods
The Hong Kong Polytechnic University · OceanBase, Ant Group · School of Management, Xi’an Jiaotong University +3
Every Client Is an Environment: Federated De-confounding for Spatio-Temporal Forecasting
Jul 27, 2026Qingxiang Liu, Anqi Liang, Heng Wang +1Spatio-Temporal Forecasting Latent Confounders
The Hong Kong University of Science and Technology (Guangzhou) · Shanghai Jiao Tong University · Harbin Engineering University
SalesLoop: Reinforcement Learning from Performance Feedback for Sales Lead Ranking
Jul 22, 2026Chenyu ZhangSales Lead Ranking
Li Auto Inc.
Dimensionality in Satisfaction Ratings
Jul 13, 2026Andrew Hong, Jason PotteigerClients Sentiment
Dimension Labs
Data-Driven Telecom Marketing Optimization: A Machine Learning-Based Churn Prediction and Customer Segmentation Framework
Jul 11, 2026Nada Ali, Lina Ahmed, Tahani Abdalla Attia GasmallaChurn Prediction Data-Driven
Department of Electrical and Electronic Engineering University of Khartoum
When Should Service Agents Reconsider? Difficulty-Routed Control in Customer-Service Operations
Jul 1, 2026Qian Chen, Chengyuan Liu, Xin YuEscalation Queue Control
†Department of Supply Chain and Information Systems · ‡Department of Statistics The Pennsylvania State University
From Complaint Narratives to Monetary Relief: A Hybrid Machine Learning Framework for CFPB Consumer Complaints
Jun 21, 2026Zhuoer Wang, Sizhen Zhu, Xiongyu ChenCredit Risk Prediction Banking
University of Illinois Urbana-Champaign · North Carolina State University · Carnegie Mellon University
Does Mixture-of-Experts Actually Help Inference on Consumer and Edge Hardware? An Empirical Study
Jun 19, 2026Alfarizy Alfarizy, Hung Truong Thanh Nguyen, René Richard +2Mixture-Of-Expert Inference Mixture-Of-Experts
Analytics Everywhere Lab, University of New Brunswick, Fredericton, NB, Canada · TSAI Lab, University of New Brunswick, Fredericton, NB, Canada
PulseCX: Breaking the Closed-World Assumption in Real-Time CX
Jun 19, 2026Rajat Agarwal, Suvidha Tripathi, Shubham SharmaConversational Artificial Intelligence Clients
Sprinklr AI, Gurugram, India
What sentiment analysis can't see: Measuring whether customers were helped, and what went wrong, across 70,000 support conversations
Jun 18, 2026Jason PotteigerSentiment Large Language Model Annotations
Dimension Labs
When Clients Stop Following: A Cognitive Conceptualization Diagram-driven Framework for Strategic Counseling
Jun 3, 2026Yihao Qin, Junyi Zhao, Changsheng Ma +4Cognitive Behavioral Therapy Counseling
School of Information Science and Engineering, Lanzhou University
Telenor Nordics Customer Service self-help corpus
May 26, 2026Mike RiessMobile Networks Text Corpora
Research and Innovation, Telenor Group, Oslo, Norway
Detecting Atypical Clients in Federated Learning via Representation-Level Divergence
May 21, 2026Cristian Pérez-Corral, Jose I. Mestre, Alberto Fernández-Hernández +2Federated Learning Divergence
Universitat Politècnica de València Valencia, Spain · Universitat Jaume I Castelló de la Plana, Spain
An Analytical Multiple Criteria Framework for Temporal and Dynamic Business-to-Business Customer Segmentation in Manufacturing
May 16, 2026Muhammad Raees, Konstantinos Papangelis, Vassilis Javed KhanManufacturing Clients
Rochester Institute of Technology Rochester NY USA · Independent Researcher
Can LLMs Think Like Consumers? Benchmarking Crowd-Level Reaction Reconstruction with ConsumerSimBench
May 16, 2026Tianyu Wang, Jiajun Li, Jianghao LinUser Simulation Clients
Shanghai Jiao Tong University · Noumena AI
A Unified Generative-AI Framework for Smart Energy Infrastructure: Intelligent Gas Distribution, Utility Billing, Carbon Analytics, and Quantum-Inspired Optimisation
May 15, 2026Pavan Manjunath, Thomas prueferGenerative Artificial Intelligence Quantum Annealing
Independent Research, India · Independent Research, Germany
FedOUI: OUI-Guided Client Weighting for Federated Aggregation
May 12, 2026Alberto Fernández-Hernández, Jose I. Mestre, Cristian Pérez-Corral +3Federated Learning Fedavg
Universitat Politècnica de València, Valencia, Spain · Universitat Jaume I, Castelló de la Plana, Spain · Openchip & Software Technologies S.L., Spain
Efficient, VRAM-Constrained xLM Inference on Clients
Apr 29, 2026Aditya Ukarande, Deep Shekhar, Marc Blackstein +1LLM Inference Optimization Shard
NVIDIA Corporation, Santa Clara, CA, USA · NVIDIA Graphics Pvt Ltd., Bangalore, India
AI as Consumer and Participant: A Co-Design Agenda for MBSE Substrates and Methodology
Apr 28, 2026Siyuan JiArtificial Intelligence Systems Co-Design
Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, UK
Generative UI as an Accessibility Bridge: Lessons from C2C E-Commerce
Apr 28, 2026Bektur RyskeldievGenerative User Interface Accessibility
Mercari R4D, Japan · University of Tsukuba, Japan
Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy
Apr 24, 2026Asim Ukaye, Mubarak Abdu-Aguye, Nurbek Tastan +1Federated Learning Contributions
MBZUAI, UAE · Michigan State University, USA
Align Generative Artificial Intelligence with Human Preferences: A Novel Large Language Model Fine-Tuning Method for Online Review Management
Apr 23, 2026Yanan Wang, Yong GePreference Alignment Learning Review
Department of Information Systems and Operations Management, The University of Texas at Arlington · Department of Management Information Systems, University of Arizona
Helping Customers in Distress: An LLM-powered Agent that Converses, Probes, and Routes
Mar 31, 2026Alankar Atreya, Stefan Sylvius Wagner, Devesh Batra +7Triage Banking
NatWest AI Research
Asynchronous Federated Continual Segmentation with Evolving Clients and Label Spaces
Mar 19, 2025Can Peng, Qianhui Men, Pramit Saha +5Federated Learning Replay-Based Continual Learning
University of Oxford, Oxford, United Kingdom · University of Bristol, Bristol, United Kingdom

Sep 30, 2026, cs.LGJ/K move · Enter open · S save

Client and Training Data Selection for Computationally Efficient Synchronized Federated Learning

Muzaffer Citir, Hiroki Nishikawa, Sangyoung Park

Smart Mobility Systems, Technical University of Berlin, Germany · Graduate School of Information Science and Technology, The University of Osaka, Japan

Federated Learning Training Data Convergence Clients Imagenet

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Federated learning (FL) is a promising paradigm of machine learning, which preserves user privacy by enabling learning without sharing raw data with a cloud server. Straggling clients have been a problem for FL as they introduce delays in aggregating the local models and hence, the convergence of the global model. Therefore, it is important to have a mechanism that ensures fast convergence of the global model as well as good FL participation rate. Another issue for the convergence of a model in FL is the non-independent and identically distributed (non-iid) data across the clients. Prior approaches based on probabilistic client selection do not work well under non-iid data especially when the number of clients is small. We show scenarios where such approaches fail and propose a joint client-training data selection algorithm for fast convergence of FL models. Our experiments on CIFAR-100 dataset show that convergence of the FL model can be significantly improved over prior works that can consider non-iid data and heterogeneous computation and higher model accuracy.

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Latest papers 32