Key papers

• Program-as-Weights: A Programming Paradigm for Fuzzy Functions (2026)
  Wentao Zhang et al.
  14.26
• Federated Adversarial Domain Adaptation (2019)
  Xingchao Peng et al.
  10.99
• Domain Arithmetic: One-Shot VLA Adaptation under Environmental Shifts (2026)
  Taewook Kang et al.
  10.83
• CausalMix: Data Mixture as Causal Inference for Language Model Training (2026)
  Zinan Tang et al.
  10.60
• A Survey on Decentralized Federated Learning (2023)
  Edoardo Gabrielli et al.
  10.32
• Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination (2026)
  Subhadeep Pal et al.
  9.48
• The State-Prediction Separation Hypothesis (2026)
  Giovanni Monea et al.
  9.11
• Discrete Diffusion Language Models for Interactive Radiology Report Drafting (2026)
  Max Van Puyvelde et al.
  7.85
• Denser $\neq$ Better: Limits of On-Policy Self-Distillation for Continual Post-Training (2026)
  Meng Wang et al.
  7.85
• Federated Domain Generalization: A Survey (2023)
  Ying Li et al.
  7.59
• Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data (2021)
  Zilong Zhao et al.
  7.50
• When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions (2023)
  Weiming Zhuang et al.
  7.50
• GRPO, Dr. GRPO, and DAPO Are Three Operations on One Number: The Group-Standard-Deviation Identity (2026)
  Yong Yi Bay et al.
  7.37
• Logit-Contribution Scoring Identifies Non-Literal Retrieval Heads (2026)
  Aryo Pradipta Gema et al.
  7.34
• Is One Layer Enough? Training A Single Transformer Layer Can Match Full-Parameter RL Training (2026)
  Zijian Zhang et al.
  7.21
• Knowledge Distillation for Federated Learning: a Practical Guide (2022)
  Alessio Mora et al.
  6.78
• Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning (2020)
  Xinjian Luo et al.
  6.66
• Personalized Semi-Supervised Federated Learning for Human Activity Recognition (2021)
  Riccardo Presotto et al.
  6.53
• Fair and efficient contribution valuation for vertical federated learning (2022)
  Zhenan Fan et al.
  6.39
• Token Geometry (2026)
  Kathan Shah
  6.37
• Purified OPSD: On-Policy Self-Distillation Without Losing How to Think (2026)
  Zhanming Shen et al.
  5.89
• How to Allocate Your Tokens? Scaling Laws with Training Steps and Batch Size (2026)
  Fabian Schaipp
  5.88
• PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark (2023)
  Jianqing Zhang et al.
  5.86
• AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks (2024)
  Zheng Lin et al.
  5.80
• Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? (2021)
  Shuxiao Chen et al.
  5.72
• Energy-Latency Attacks via Sponge Poisoning (2022)
  Antonio Emanuele Cin\`a et al.
  5.72
• A Mechanism-Driven Theory of Phase Transitions in Active Learning (2026)
  Julia Machnio et al.
  5.49
• Steal the Patch Size: Adversarially Manipulate Vision-Language Models (2026)
  Kai Hu et al.
  5.49
• Rosetta: Composable Native Multimodal Pretraining (2026)
  Xiangyue Liu et al.
  5.49
• When AI meets quantum information: A comprehensive review (2026)
  Min Chen et al.
  5.49
• SAOT: Self-Supervised Continual Graph Learning with Structure-Aware Optimal Transport (2026)
  Yuting Zhang et al.
  5.49
• The Illusion of High Utility in Safety Alignment of Text-to-Image Diffusion Models (2026)
  Adeel Yousaf et al.
  5.49
• Information-Regularized Attention for Visual-Centric Reasoning (2026)
  Guohao Sun et al.
  5.49
• StochasT: Learning with Stochastic Turn Depth for Visual Instruction Tuning (2026)
  Yuan Qing et al.
  5.49
• LUMA: Benchmarking Segmentation via a Lightweight Universal Mask Adapter (2026)
  Tobias Christian Nauen et al.
  5.49
• Foundation Models vs. Radiomics for Lung Computed Tomography: A Benchmark of Feature Extractors, Classification Heads, and Segmentation Choices (2026)
  Nils Neukirch et al.
  5.49
• QuasiMoTTo: Quasi-Monte Carlo Test-Time Scaling (2026)
  Michael Y. Li et al.
  5.49
• Boundary-Aware Quantization: Finite-Scale Decision Geometry of Neural Classifiers (2026)
  O. M. Kiselev
  5.49
• Mean Field Reinforcement Learning (2026)
  Ren\'e Carmona et al.
  5.49
• Stable Self-Modulating Quantum Fast-Weight Programmers with Bounded Memory Gates (2026)
  Kuo-Chung Peng et al.
  5.49
• Optimal Stabilizer Testing and Learning with Limited Quantum Memory (2026)
  Srinivasan Arunachalam et al.
  5.49
• LACUNA: A Testbed for Evaluating Localization Precision for LLM Unlearning (2026)
  Matteo Boglioni et al.
  5.49
• Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems (2025)
  William Marfo et al.
  5.48
• Quantum-secure multiparty deep learning (2024)
  Kfir Sulimany et al.
  5.29
• Federated Learning with Sample-level Client Drift Mitigation (2025)
  Haoran Xu et al.
  5.13
• FedDTG:Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks (2022)
  Lingzhi Gao et al.
  5.06
• Federated Transfer Learning with Differential Privacy (2024)
  Mengchu Li et al.
  5.02
• EVOTS: Evolutionary Transformer Search for Time Series Forecasting (2026)
  AbdElRahman ElSaid et al.
  5.01
• Scaling Up Thermodynamic AI Models (2026)
  Andrew G. Moore
  5.01
• Distributionally Robust Linear Regression With Block Lewis Weights (2026)
  Naren Sarayu Manoj et al.
  5.01
• Testing Frontier Large Language Models' Physics Literacy in Parallel Physical Worlds (2026)
  Dong Zhang
  5.01
• Self-Organized Learning in Oscillatory Neural Networks with Memristive Signed Couplings (2026)
  Riley Acker et al.
  5.01
• Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization (2026)
  Xuefeng Liu et al.
  5.01
• ZO-Act: Efficient Zeroth-Order Fine-Tuning via One-Shot Activation-Informed Low-Rank Subspaces (2026)
  Xun Dong et al.
  5.01
• Right in the Right Way: LM Training with Verifiable Rewards and Human Demonstrations (2026)
  Mehul Damani et al.
  5.01
• GPU-Parallel Linearization Error Bounds for Real-Time Robust Optimal Control of Nonlinear and Neural Network Dynamics (2026)
  Jeffrey Fang et al.
  5.01
• Theoria: Rewrite-Acceptability Verification over Informal Reasoning States (2026)
  Michael Saldivar et al.
  5.01
• Language-Critique Imitation Learning from Suboptimal Demonstrations (2026)
  Chih-Han Yang et al.
  5.01
• Fast approximation and learning of binary classification tasks in o-minimal structures using ReLU neural networks (2026)
  Clemens Kinn et al.
  5.01
• Ravines in quantum cost landscapes: opportunities for improved VQA predictions (2026)
  Felix J. Beckmann et al.
  5.01