| 1 | Closing the Horizon Gap in Policy Optimization for Adversarial MDPs | Mingyi Li, Taira Tsuchiya | cs.LG | 2026-10-08 |
| 2 | Spatial Pattern Formation from Multi-Agent Learning in Public Goods Dilemmas | Yefei Zhang, Yuxuan Zhao | cs.MA | 2026-10-08 |
| 3 | Test-Time Compute for Tabular Foundation Models: Mechanisms, Gains, and Limits | Kanghui Ning, Marin Biloš, James T. Wilson +5 | cs.LG | 2026-10-08 |
| #4 | Interval-valued SHAP in Tree-Based Models | Chenrui Zhu, Vu-Linh Nguyen, Marie-Hélène Masson +1 | cs.LG | 2026-10-08 |
| #5 | Cost-Aware Mixture-of-Experts Coordination for Model Markets | Yizhou Ma, Wenbo Wu, Xikun Jiang +2 | cs.DB | 2026-10-08 |
| #6 | Compile the Table: Query-Calibrated Operator Compression for Tabular In-Context Learning | Xu Zhao, Jiaming Zhao, Bin Zhao +1 | cs.LG | 2026-10-08 |
| #7 | LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression | Rahul Goswami, Aryan Bhambu, Bittu Karmakar | stat.ML | 2026-10-08 |
| #8 | MC-TRCM: Observation-Aware Recursive Fusion for Incomplete Mobile and Wearable Mental-Health Feature Views | Wentao Wang, Lifeng Han, Zining Ren +2 | cs.LG | 2026-10-08 |
| #9 | Beyond Distributional Fidelity: Causal-Penalized Diffusion for Synthetic Tabular Data | Lan Tao, Yongxian He, Shirong Xu +2 | stat.ML | 2026-10-08 |
| #10 | Machine Learning Optimization for Enhanced OS Fingerprinting | Jae Sung Kim, Spencer Ekeroth, Jeremy Neale | cs.LG | 2026-10-08 |
| #11 | MotherTree: Meta-learning on synthetic data improves decision tree training | Ziyuan Wang, Fredrik D. Johansson | cs.LG | 2026-10-07 |
| #12 | Conversational Task Disambiguation over Tabular Data: Leakage-Aware Formulation, Benchmark Suite, and Training | Nafiseh Ghoroghchian, Luis Scoccola, Tina Sedaghat +4 | cs.LG | 2026-10-07 |
| #13 | Evolutionary Architecture Search for Chlorophyll-$a$ Prediction in Lakes using Sentinel-2 | Kursat Komurcu, Linas Petkevicius | cs.NE | 2026-10-07 |
| #14 | Estimating Uncoded Crash Factors with Tabular Foundation and System One Models: Kumo Tabular and Jev | Amir Rafe, Subasish Das | stat.AP | 2026-10-07 |
| #15 | Thinking in Depth: Retrospective Inference for Tabular Foundation Models | Hao-Run Cai, Si-Yang Liu, Zi-Jian Cheng +8 | cs.LG | 2026-10-07 |
| #16 | A Closed-Loop Non-Asymptotic Convergence Analysis of PPO with Learned Critics and Clipping | Junwei Su, Mengfan Liu, Yanyong Zhang +1 | cs.LG | 2026-10-07 |
| #17 | From Prompts to Trees: Effective LLM-Guided Tree Generation for Few-Shot Tabular Classification | Yue Qiu, Zekang Du, Yiqun Diao +2 | cs.LG | 2026-10-07 |
| #18 | Efficient Provably Private Classification with a Tabular Foundation Model | Talal Alrawajfeh, Cristiana Diaconu, Ossi Räisä +5 | cs.LG | 2026-10-07 |
| #19 | Phase-HDC: Replacing Optimizer History with Gradient Thresholds in Discrete Phase Learning | Ahmed Nebli | cs.LG | 2026-10-07 |
| #20 | Scalable Logistic Gaussian Process Density Regression with Kinetic Langevin Sampling | Daniel Paulin, Ádám Jung, András A. Benczúr | stat.ML | 2026-10-07 |
| #21 | Neighborhood Smoothing for Calibration | Idan Horowitz, Avigdor Gal | cs.LG | 2026-10-06 |
| #22 | GeneICL: A Tabular Foundation Model for Bulk Transcriptomics | Michael Bohl, Alexander Theus, David Wissel +1 | cs.LG | 2026-10-06 |
| #23 | Valid for Free: Homophily-Gated Conformal Prediction for Training-Free Node Classification with Tabular Foundation Models | Nguyen Duy Long, Phung Minh Hien, Nguyen Trong Viet +1 | cs.LG | 2026-10-06 |
| #24 | FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching | Emmanouil Panagiotou, Eirini Ntoutsi | cs.LG | 2026-10-06 |
| #25 | The Standardization Trap: Certifying Joint Label Processing in Tabular Foundation Models | Duong Nguyen, Nicolas Chesneau, Milan Bhan | cs.AI | 2026-10-06 |
| #26 | Scalable extraction and visualization of multi-attribute logical and functional dependencies in tabular data | Chaithra Umesh, Arvind Lomrore, Neethu D +3 | cs.LG | 2026-10-06 |
| #27 | ProximalFM: Amortized Proximal Causal Inference under Hidden Confounding | Christophe Muller, Ayub Kharel, Alex Luedtke +6 | stat.ML | 2026-10-06 |
| #28 | TICDA: Tabular In-Context Data Attribution | Yacine Benihaddadene, Milan Bhan, Eliot Dugelay +4 | cs.LG | 2026-10-06 |
| #29 | TAFFY: A Task-Adaptive Tabular Foundation Model with In-Context Diversity | Zijian Li, Xiangchen Song, Gongxu Luo +7 | cs.LG | 2026-10-06 |
| #30 | Evaluation of Active Feature Acquisition Policies with Tabular Foundation Models | Yuta Kobayashi, Divyam Madaan, Shalmali Joshi | cs.LG | 2026-10-05 |
| #31 | Exact Unlearning via Quantized Sufficient Statistics | Ami Tavory, Shripad Gade, Tal Sarig +2 | cs.LG | 2026-10-05 |
| #32 | MatrixFormer: A Foundation Model for Matrix Completion | Dwaipayan Saha, Jacob Feitelberg, Kyuseong Choi +2 | cs.LG | 2026-10-05 |
| #33 | Adapting prior-data fitted networks for tabular anomaly detection | Maximilian Bershtman, Niv Cohen | cs.LG | 2026-10-05 |
| #34 | Closing the Context Gap: Activation Alignment for Tabular In-Context Learning | Yoel Zeldes | cs.LG | 2026-10-05 |
| #35 | TIGER: Time-Series Classification with In-Context-Learning Gated Ensemble of Representations | Johann Faouzi | cs.LG | 2026-10-05 |
| #36 | On the Geometry of Multimodal Saturation: Riemannian VICReg | Nessim Ben Abbes, Duc Han Le, Sabri Mtibaa +1 | cs.LG | 2026-10-05 |
| #37 | MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting | Ilya Kuleshov, Egor Serov, Alexey Zaytsev | cs.LG | 2026-10-05 |
| #38 | CCQ: A Multi-State Child Care Quality Dataset to Support AI for Children's Health Research | Victor Li, Yuzhang Xie, Ziwei Dong +6 | cs.LG | 2026-10-05 |
| #39 | The Blind Spot Paradox: When Adaptive Classifiers Defeat Drift Detectors | Raphaël Minato, Fabrice Popineau, Arpad Rimmel +1 | cs.LG | 2026-10-05 |
| #40 | HiER-BLS: A Hierarchy-Guided and Error-Correcting Robust Incremental Broad Learning System | Gongli Zhang, C. L. Philip Chen, Zhulin Liu | cs.LG | 2026-10-05 |
| #41 | Usefulness of Quantile-Aware Diffusion Modeling for Highly Imbalanced Tabular Data | Abu Talha, Peng Liu, Souradyuti Paul | cs.LG | 2026-10-05 |
| #42 | An equality condition for the Dobrushin bound on attention rollout and how often it holds in trained transformers | Przemysław Rola | cs.LG | 2026-10-04 |
| #43 | Rethinking Tabular Foundation Models On Data Streams | Nilesh Verma, Daniel Nowak-Assis, Afonso Lourenço +4 | cs.LG | 2026-10-04 |
| #44 | Learning under Localized Minority Imbalance | Amin Hosseininasab, Steven M. Shugan | cs.LG | 2026-10-04 |
| #45 | DASH: Fast, Valid Counterfactuals for Deep Networks via Batched Directional Search | Shraman Pal, Gabriel Medeiros, Clayton Escouper das Chagas +1 | cs.LG | 2026-10-03 |
| #46 | Variance-Aware Fine-Grained Gap-Dependent Bounds for Online Reinforcement Learning | Haochen Zhang, Lingzhou Xue, Zhong Zheng | stat.ML | 2026-10-03 |
| #47 | Exact Fast Batch Simulation for Tabular Reinforcement Learning | Haochen Zhang, Lingzhou Xue, Zhong Zheng | stat.ML | 2026-10-03 |
| #48 | Do RUL explanations hold up? Faithfulness and stability of attributions on C-MAPSS | Manh Hien Nguyen, Ngoc Thanh Nguyen, Isabella Mendoza Cortes +5 | cs.LG | 2026-10-03 |
| #49 | Integrated Imputation-Classification for Supervised Learning with Missing Data | Yue Liu, Ben Liang, Ali Tizghadam +1 | cs.LG | 2026-10-03 |
| #50 | Below what training size do deep tabular generators stop beating trivial baselines? A preregistered benchmark on a size ladder of clinical and standard datasets | Shivam Shrivastava | cs.LG | 2026-10-02 |