NeurIPS 2024 Past Tabular & structured data

NeurIPS 2024 Third Table Representation Learning Workshop

TRL @ NeurIPS 2024

Submission deadline
Sep 23, 2024, 18:00 UTC
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Submission portal
OpenReview
Notes
Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).

Accepted papers (59)

Fetched from OpenReview (v2) on 2026-06-10.

  1. AdapTable: Test-Time Adaptation for Tabular Data via Shift-Aware Uncertainty Calibrator and Label Distribution Handler

    Changhun Kim, Taewon Kim, Seungyeon Woo, June Yong Yang, Eunho Yang · PDF
  2. Adapting TabPFN for Zero-Inflated Metagenomic Data

    Giulia Perciballi, Federica Granese, Ahmad Fall, Farida ZEHRAOUI, Edi Prifti, Jean-Daniel Zucker · PDF
  3. AGATa: Attention-Guided Augmentation for Tabular Data in Contrastive Learning

    Moonjung Eo, Kyungeun Lee, Min-Kook Suh, Hye-Seung Cho, Ye Seul Sim, Woohyung Lim · PDF
  4. Augmenting Small-size Tabular Data with Class-Specific Energy-Based Models

    Andrei Margeloiu, Xiangjian Jiang, Nikola Simidjievski, Mateja Jamnik · PDF
  5. Automating Enterprise Data Engineering with LLMs

    Jan-Micha Bodensohn, Ulf Brackmann, Liane Vogel, Anupam Sanghi, Carsten Binnig · PDF
  6. Benchmarking table comprehension in the wild

    Yikang Pan, Yi Zhu, Rand Xie, Yizhi Liu · PDF
  7. Data-Centric Text-to-SQL with Large Language Models

    Zezhou Huang, Shuo Zhang, Kechen Liu, Eugene Wu · PDF
  8. Distributionally robust self-supervised learning for tabular data

    Shantanu Ghosh, Tiankang Xie, Mikhail Kuznetsov · PDF
  9. Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data

    David Schnurr, Kai Helli, Noah Hollmann, Samuel Müller, Frank Hutter · PDF
  10. DynoClass: A Dynamic Table-Class Detection System Without the Need for Predefined Ontologies

    Haonan Wang, Eugene Wu, Kechen Liu, Jiaxiang Liu · PDF
  11. Enhancing Biomedical Schema Matching with LLM-based Training Data Generation

    Yurong Liu, Aécio Santos, Eduardo H. M. Pena, Roque Lopez, Eden Wu, Juliana Freire · PDF
  12. Enhancing Table Representations with LLM-powered Synthetic Data Generation

    Dayu Yang, Natawut Monaikul, Amanda Ding, Bozhao Tan, Kishore Mosaliganti, Giri Iyengar · PDF
  13. Expertise-Centric Prompting Framework for Financial Tabular Data Generation using Pre-trained Large Language Models

    Subin Kim, Jungmin Son, Minyoung Jung, Youngjun Kwak · PDF
  14. Exploration of autoregressive models for in-context learning on tabular data

    Stefan K. Baur, Sohyeong Kim · PDF
  15. From One to Zero: RAG-IM Adapts Language Models for Interpretable Zero-Shot Predictions on Clinical Tabular Data

    Sazan Mahbub, Caleb Ellington, Sina Alinejad, Kevin Wen, Yingtao Luo, Ben Lengerich, Eric P. Xing · PDF
  16. GAMformer: Exploring In-Context Learning for Generalized Additive Models

    Andreas C Mueller, Julien Siems, Harsha Nori, David Salinas, Arber Zela, Rich Caruana, Frank Hutter · PDF
  17. HySem: A context length optimized LLM pipeline for unstructured tabular extraction

    Narayanan PP, Anantharaman Palacode Narayana Iyer · PDF
  18. ICE-T: Interactions-aware Cross-column Contrastive Embedding for Heterogeneous Tabular Datasets

    Tomas Tokar, Scott Sanner · PDF
  19. Improving LLM Group Fairness on Tabular Data via In-Context Learning

    Valeriia Cherepanova, Chia-Jung Lee, Nil-Jana Akpinar, Riccardo Fogliato, Martin Andres Bertran, Michael Kearns, James Zou · PDF
  20. Large Language Models Engineer Too Many Simple Features for Tabular Data

    Jaris Küken, Lennart Purucker, Frank Hutter · PDF
  21. Learnable Numerical Input Normalization for Tabular Representation Learning based on B-splines

    Min-Kook Suh, Moonjung Eo, Ye Seul Sim, Woohyung Lim · PDF
  22. Learning Metadata-Agnostic Representations for Text-to-SQL In-Context Example Selection

    Chuhong Mai, Ro-ee Tal, Thahir Mohamed · PDF
  23. Lightweight Correlation-Aware Table Compression

    Mihail Stoian, Alexander van Renen, Jan Kobiolka, Ping-Lin Kuo, Josif Grabocka, Andreas Kipf · PDF
  24. LLM Embeddings Improve Test-time Adaptation to Tabular $Y|X$-Shifts

    Yibo Zeng, Jiashuo Liu, Henry Lam, Hongseok Namkoong · PDF
  25. Matchmaker: Self-Improving Compositional LLM Programs for Table Schema Matching

    Nabeel Seedat, Mihaela van der Schaar · PDF
  26. MotherNet: Fast Training and Inference via Hyper-Network Transformers

    Andreas C Mueller, Carlo A Curino, Raghu Ramakrishnan · PDF
  27. MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation

    Satya Krishna Gorti, Ilan Gofman, Zhaoyan Liu, Jiapeng Wu, Noël Vouitsis, Guangwei Yu, Jesse C. Cresswell, Rasa Hosseinzadeh · PDF
  28. Multi-Stage QLoRA with Augmented Structured Dialogue Corpora: Efficient and Improved Conversational Healthcare AI

    Dasun Athukoralage, Thushari Atapattu · PDF
  29. On Short Textual Value Column Representation Using Symbol Level Language Models

    Ron Begleiter, Nathan Roll · PDF
  30. PORTAL: Scalable Tabular Foundation Models via Content-Specific Tokenization

    Marco Spinaci, Marek Polewczyk, Johannes Hoffart, Markus C. Kohler, Sam Thelin, Tassilo Klein · PDF
  31. PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning

    Weihua Hu, Yiwen Yuan, Zecheng Zhang, Akihiro Nitta, Kaidi Cao, Vid Kocijan, Jinu Sunil, Jure Leskovec, Matthias Fey · PDF
  32. RACOON: An LLM-based Framework for Retrieval-Augmented Column Type Annotation with a Knowledge Graph

    Lindsey Linxi Wei, Guorui Xiao, Magdalena Balazinska · PDF
  33. Recurrent Interpolants for Probabilistic Time Series Prediction

    Yu Chen, Marin Biloš, Sarthak Mittal, Wei Deng, Kashif Rasul, Anderson Schneider · PDF
  34. Relational Data Generation with Graph Neural Networks and Latent Diffusion Models

    Valter Hudovernik · PDF
  35. Relational Deep Learning: Graph Representation Learning on Relational Databases

    Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec · PDF
  36. SALT: Sales Autocompletion Linked Business Tables Dataset

    Tassilo Klein, Clemens Biehl, Margarida Costa, Andre Sres, Jonas Kolk, Johannes Hoffart · PDF
  37. Scalable Representation Learning for Multimodal Tabular Transactions

    Natraj Raman, Sumitra Ganesh, Manuela Veloso · PDF
  38. Scaling Generative Tabular Learning for Large Language Models

    Yiming Sun, Xumeng Wen, Shun Zheng, Xiaowei Jia, Jiang Bian · PDF
  39. Sparsely Connected Layers for Financial Tabular Data

    Mohammed Abdulrahman, Hui Chen, Yin WANG · PDF
  40. SynQL: Synthetic Data Generation for In-Domain, Low-Resource Text-to-SQL Parsing

    Denver Baumgartner, Tomasz Kornuta · PDF
  41. Synthetic SQL Column Descriptions and Their Impact on Text-to-SQL Performance

    Niklas Wretblad, Oskar Holmström, Erik Larsson, Axel Wiksäter, Hjalmar Öhman, Oscar Söderlund, Ture Pontén, Martin Forsberg, Martin Sörme, Fredrik Heintz · PDF
  42. Tabby: Tabular Adaptation for Language Models

    Sonia Cromp, Satya Sai Srinath Namburi GNVV, Catherine Cao, Mohammed Alkhudhayri, Samuel Guo, Nicholas Roberts, Frederic Sala · PDF
  43. TabDeco: A Comprehensive Contrastive Framework for Decoupled Representations in Tabular Data

    Suiyao Chen, Jing Wu, Yunxiao Wang, Cheng Ji, Tianpei Xie, Daniel Cociorva, Michael Sharps, Cecile Levasseur, Hakan Brunzell · PDF
  44. TabDiff: a Unified Diffusion Model for Multi-Modal Tabular Data Generation

    Juntong Shi, Minkai Xu, Harper Hua, Hengrui Zhang, Stefano Ermon, Jure Leskovec · PDF
  45. TabFlex: Scaling Tabular Learning to Millions with Linear Attention

    Yuchen Zeng, Wonjun Kang, Andreas C Mueller · PDF
  46. TABGEN-RAG: Iterative Retrieval for Tabular Data Generation with Large Language Models

    Liancheng Fang, Aiwei Liu, Hengrui Zhang, Henry Peng Zou, Weizhi Zhang, Philip S. Yu · PDF
  47. TabGraphs: A Benchmark and Strong Baselines for Learning on Graphs with Tabular Node Features

    Gleb Bazhenov, Oleg Platonov, Liudmila Prokhorenkova · PDF
  48. TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes

    Aamod Khatiwada, Harsha Kokel, Ibrahim Abdelaziz, Subhajit Chaudhury, Julian Dolby, Oktie Hassanzadeh, Zhenhan Huang, Tejaswini Pedapati, Horst Samulowitz, Kavitha Srinivas · PDF
  49. Tabular Data Generation using Binary Diffusion

    Vitaliy Kinakh, Slava Voloshynovskiy · PDF
  50. TARGET: Benchmarking Table Retrieval for Generative Tasks

    Xingyu Ji, Aditya Parameswaran, Madelon Hulsebos · PDF
  51. TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning

    Xinyuan Lu, Liangming Pan, Yubo Ma, Preslav Nakov, Min-Yen Kan · PDF
  52. The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models

    Karime Maamari, Fadhil Abubaker, Daniel Jaroslawicz, Amine Mhedhbi · PDF
  53. The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features

    Shi Bin Hoo, Samuel Müller, David Salinas, Frank Hutter · PDF
  54. Towards Agentic Schema Refinement

    Agapi Rissaki, Ilias Fountalis, Nikolaos Vasiloglou, Wolfgang Gatterbauer · PDF
  55. Towards Localization via Data Embedding for TabPFN

    Mykhailo Koshil, Thomas Nagler, Matthias Feurer, Katharina Eggensperger · PDF
  56. Towards Optimizing SQL Generation via LLM Routing

    Mohammadhossein Malekpour, Nour Shaheen, Foutse Khomh, Amine Mhedhbi · PDF
  57. UniTable: Towards a Unified Framework for Table Recognition via Self-Supervised Pretraining

    ShengYun Peng, Aishwarya Chakravarthy, Seongmin Lee, Xiaojing Wang, Rajarajeswari Balasubramaniyan, Duen Horng Chau · PDF
  58. Unlearning Tabular Data Without a "Forget Set''

    Aviraj Newatia, Michael Cooper, Rahul Krishnan · PDF
  59. Unmasking Trees for Tabular Data

    Calvin McCarter · PDF