Tabular ICL

ICL: In-Context Learning

Momentum

9 papers in the last four weeks, up 125% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 68

All topics
CardsList
  1. Thinking in Depth: Retrospective Inference for Tabular Foundation Models

    Oct 7, 2026Hao-Run Cai, Si-Yang Liu, Zi-Jian Cheng +8Tabular Foundation ModelsTabular ICL

  2. GeneICL: A Tabular Foundation Model for Bulk Transcriptomics

    Oct 6, 2026Michael Bohl, Alexander Theus, David Wissel +1Tabular Foundation ModelsClinical Outcome Prediction

  3. TICDA: Tabular In-Context Data Attribution

    Oct 6, 2026Yacine Benihaddadene, Milan Bhan, Eliot Dugelay +4Tabular Foundation ModelsTabular ICL

  4. TAFFY: A Task-Adaptive Tabular Foundation Model with In-Context Diversity

    Oct 6, 2026Zijian Li, Xiangchen Song, Gongxu Luo +7Synthetic Data PretrainingTabular Foundation Models

  5. Rethinking Tabular Foundation Models On Data Streams

    Oct 4, 2026Nilesh Verma, Daniel Nowak-Assis, Afonso Lourenço +4Tabular Foundation ModelsTabular ICL

  6. LoopICL: Looping a single transformer block to solve tabular tasks

    Sep 28, 2026Amir Rezaei Balef, Katharina EggenspergerTabular Foundation ModelsCost-Aware Inference

  7. Benchmarking Attention for Tabular Foundation Models

    Sep 25, 2026Maximilian Schambach, Clemens Biehl, Sam ThelinTabular Foundation ModelsEfficient Attention

  8. SwitchPFN: Shared Switching Dynamics for Frozen In-Context Time Series Classification

    Sep 24, 2026Zhenyi Zhu, Jacqueline Pang, Peilin Shen +7Tabular Foundation ModelsTime Series Classification

  9. TabPFN-3.5: Technical Report

    Sep 15, 2026Benjamin Jäger, Nick Erickson, Léo Grinsztajn +44Tabular Foundation ModelsInference-Time Optimization

  10. Balanced Adaptive Prototype Selection for Scalable TabPFN Inference on Large-Scale Tabular Data

    Aug 13, 2026Mahboobe Jadid, Melika Rezaye Garkani, Ali MousaviTabular Foundation ModelsTabular ICL

  11. TACTICL: Task-Aware Compression of Tabular ICL Models

    Aug 11, 2026Mykhailo Koshil, Matthias Feurer, Katharina EggenspergerModel CompressionTabular Foundation Models

  12. In-Context Density Estimation for Tabular Data

    Aug 10, 2026Patryk Marszałek, Jacek Tabor, Marek ŚmiejaEnergy-Based ModelsUnsupervised Anomaly Detection

  13. EdgeLM: Edge Demonstrations for Language Models' Table Understanding

    Aug 5, 2026Soroush Omidvartehrani, Mohammadamin Habibollah, Mohammadreza Daviran +1In-Context Example SelectionIn-Context Learning

  14. Enhancing Tabular Learners with Context-Aware Semantic Embeddings

    Aug 4, 2026Günther Schindler, Maximilian Schambach, Johannes HöhneTabular Foundation ModelsRepresentation Learning

  15. TabDPT-Turbo: Efficient In-Context Learning for Tabular Prediction

    Aug 2, 2026Rasa Hosseinzadeh, Alex Labach, Zexin Xue +3Tabular Foundation ModelsTabular ICL

  16. Memory Efficient Tabular Foundation Models

    Jul 30, 2026Shuting Luo, Monika Mikhail Kanaan, Cameron Gordon +2Model CompressionTabular Foundation Models

  17. Understanding Context Sampling in TabPFN on Small Tabular Datasets

    Jul 29, 2026Mohammed AbdullahTabular Foundation ModelsTabular Classification

  18. Entangled by Design: Spurious Intra-Variable Signal Routing in Tabular In-Context Learners

    Jul 28, 2026Athanasios Vlontzos, Giorgos Papanastasiou, Bernhard Kainz +1Spurious Correlation RobustnessTabular ICL

  19. In-Context Time Series Classification with Random Convolutional Features

    Jul 21, 2026Joscha Cüppers, Jilles VreekenTabular Foundation ModelsTime Series Classification

  20. Topological Signatures of Context-Level Reliability in TabPFN

    Jul 20, 2026James Hu, Mahdi GhelichiTabular Foundation ModelsNeural Representation Geometry

  21. Tabular Foundation Models for Discrete Choice Estimation

    Jul 14, 2026Liu Liu, Dan ZhangTabular Foundation ModelsDiscrete Choice Modeling

  22. TabPATE: Differentially Private Tabular In-Context Learning Without Public Data

    Jun 30, 2026Dariush Wahdany, Matthew Jagielski, Jesse C. Cresswell +2Tabular Foundation ModelsDifferential Privacy

  23. Probing Memorization of Tabular In-Context Learning

    Jun 30, 2026Francesco Capano, Jonas BöhlerTabular Foundation ModelsMembership Inference Attacks

  24. Can Tabular In-Context Learners Generalize to Biomolecular Property Prediction?

    Jun 30, 2026Davy Guan, Lu Zhang, Asiri Wijesinghe +7Tabular Foundation ModelsProtein Fitness Prediction

  25. Are Tabular Foundation Models Robust to Realistic Query Distribution Shifts in Microbiome Data?

    Jun 23, 2026Giulia Perciballi, Ahmad Fall, Federica Granese +2Distribution Shift RobustnessTabular Foundation Models

  26. Bounded Context Management for Tabular Foundation Models on Stream Learning

    Jun 17, 2026Jinmo Lee, Doyun Choi, Moongi Choi +1In-Context Example SelectionTabular Foundation Models

  27. Where Computation Lives Inside TabPFN: Causal Localisation of Attention Head Function

    Jun 11, 2026Atharva Gupta, Dhruv Kumar, Murari Mandal +1Tabular Foundation ModelsAttention Head Analysis

  28. CRUMB: Efficient Prior Fitted Network Inference via Distributionally Matched Context Batching

    Jun 9, 2026Jamie Heredge, Mattia J. Villani, Pranav Deshpande +2In-Context LearningPrior-Data Fitted Networks

  29. In-Context Learning for Latent Space Bayesian Optimization

    Jun 8, 2026Tuan A. Vu, Harri Lähdesmäki, Julien MartinelliSynthetic Data PretrainingMolecular Optimization

  30. In-Context Learning for the Imputation of Public Opinion Data with Large Language Models

    Jun 8, 2026Tobias Holtdirk, Georg Ahnert, Joseph W Sakshaug +1Incomplete Data ImputationLearning with Missing Data

  31. TabSwift: An Efficient Tabular Foundation Model with Row-Wise Attention

    Jun 5, 2026Si-Yang Liu, Han-Jia YeTabular Foundation ModelsEfficient Inference

  32. Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models

    Jun 3, 2026Raffael Theiler, Lev Telyatnikov, Leandro Von Krannichfeldt +1Tabular Foundation ModelsRUL Estimation

  33. OpenRFM: Dissecting Relational In-Context Learning

    Jun 3, 2026Zhikai Chen, Junyu Yin, Jialiang Gu +5Relational Foundation ModelsSynthetic Data Pretraining

  34. Algorithmic Recourse of In-Context Learning for Tabular Data

    May 29, 2026Wenshuo Dong, Jiaming Zhang, Shaopeng Fu +3Tabular ICLAlgorithmic Recourse

  35. LUCoS: Latent Unsupervised Context Selection for Tabular Foundation Models

    May 26, 2026Oroel Ipas, Guillermo Gomez-Trenado, Rocío Romero-Zaliz +1Tabular Foundation ModelsTabular ICL

  36. LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots

    May 23, 2026Daria Grushina, Kseniia Kuvshinova, Alina Kostromina +3Zero-Shot LearningLLM Evaluation

  37. Is TabPFN the Silver Bullet for Insurance Pricing?

    May 21, 2026Bruno Deprez, Wouter Verbeke, Tim VerdonckTabular Foundation ModelsTabular ICL

  38. Learning Causal Orderings for In-Context Tabular Prediction

    May 21, 2026Sascha Xu, Sarah Mameche, Jilles VreekenIncomplete Data ImputationCausal Structure Learning

  39. A Mechanistic Study of Tabular Foundation Models

    May 20, 2026Marin Biloš, James T. Wilson, Anderson Schneider +1Tabular Foundation ModelsMechanistic Interpretability

  40. When Tabular Foundation Models Meet Strategic Tabular Data: A Prior Alignment Approach

    May 19, 2026Xinpeng Lv, Yunxin Mao, Renzhe Xu +13Tabular Foundation ModelsStrategic Classification

  41. TabQL: In-Context Q-Learning with Tabular Foundation Models

    May 18, 2026Qisai Liu, Zhanhong Jiang, Timilehin Ayanlade +4Deep Q-LearningQ-Learning

  42. TabPFN-MT: A Natively Multitask In-Context Learner for Tabular Data

    May 16, 2026Cormac Cureton, Narges ArmanfardTabular Foundation ModelsEfficient Neural Network Inference

  43. TabPFN-3: Technical Report

    May 13, 2026Léo Grinsztajn, Klemens Flöge, Oscar Key +38Tabular Foundation ModelsEfficient Neural Network Inference

  44. VIP-COP: Context Optimization for Tabular Foundation Models

    May 13, 2026Yilong Chen, Xueying Ding, Leman AkogluIn-Context Example SelectionTabular Foundation Models

  45. PromptDx: Differentiable Prompt Tuning for Multimodal In-Context Alzheimer's Diagnosis

    May 9, 2026Lujia Zhong, Yihao Xia, Shuo Huang +2Multimodal ICLMedical Diagnosis