Why Tabular Foundation Models Should Be a Research Priority

2 May 2024

Papers citing "Why Tabular Foundation Models Should Be a Research Priority"

33 / 33 papers shown

Title
TabSTAR: A Foundation Tabular Model With Semantically Target-Aware Representations Alan Arazi Eilam Shapira Roi Reichart LMTD 166 0 0 23 May 2025
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners Kezhi Kong Jiani Zhang Zhengyuan Shen Balasubramaniam Srinivasan Chuan Lei Christos Faloutsos Huzefa Rangwala George Karypis LMTD ReLM RALM LRM 85 17 0 22 Feb 2024
TabuLa: Harnessing Language Models for Tabular Data Synthesis Zilong Zhao Robert Birke Lydia Y. Chen LMTD 83 30 0 19 Oct 2023
From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models Xumeng Wen Han Zhang Shun Zheng Wei Xu Jiang Bian LMTD ALM 97 21 0 11 Oct 2023
CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets Lifan Yuan Yangyi Chen Xingyao Wang Yi R. Fung Hao Peng Heng Ji LLMAG KELM 88 65 0 29 Sep 2023
UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science Yazheng Yang Yuqi Wang Guangyi Liu Ledell Yu Wu Qi Liu LMTD 56 17 0 18 Jul 2023
XTab: Cross-table Pretraining for Tabular Transformers Bingzhao Zhu Xingjian Shi Nick Erickson Mu Li George Karypis Mahsa Shoaran LMTD 76 70 0 10 May 2023
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering Noah Hollmann Samuel G. Müller Frank Hutter 67 58 0 05 May 2023
When Do Neural Nets Outperform Boosted Trees on Tabular Data? Duncan C. McElfresh Sujay Khandagale Jonathan Valverde C. VishakPrasad Ben Feuer Chinmay Hegde Ganesh Ramakrishnan Micah Goldblum Colin White LMTD 64 154 0 04 May 2023
Beyond Privacy: Navigating the Opportunities and Challenges of Synthetic Data B. V. Breugel M. Schaar 43 30 0 07 Apr 2023
LEVER: Learning to Verify Language-to-Code Generation with Execution Ansong Ni Srini Iyer Dragomir R. Radev Ves Stoyanov Wen-tau Yih Sida I. Wang Xi Lin 59 223 0 16 Feb 2023
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation Josh Gardner Zoran Popovic Ludwig Schmidt OOD 82 23 0 23 Nov 2022
Language Models are Realistic Tabular Data Generators V. Borisov Kathrin Seßler Tobias Leemann Martin Pawelczyk Gjergji Kasneci LMTD 68 247 0 12 Oct 2022
Why do tree-based models still outperform deep learning on tabular data? Léo Grinsztajn Edouard Oyallon Gaël Varoquaux LMTD 74 366 0 18 Jul 2022
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 82 301 0 05 Jul 2022
Synthetic Data -- what, why and how? James Jordon Lukasz Szpruch F. Houssiau M. Bottarelli Giovanni Cherubin Carsten Maple Samuel N. Cohen Adrian Weller 67 115 0 06 May 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 365 15,373 0 20 Dec 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 98 681 0 05 Oct 2021
Revisiting Deep Learning Models for Tabular Data Yu. V. Gorishniy Ivan Rubachev Valentin Khrulkov Artem Babenko LMTD 98 720 0 22 Jun 2021
Tabular Data: Deep Learning is Not All You Need Ravid Shwartz-Ziv Amitai Armon LMTD 149 1,256 0 06 Jun 2021
SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training Gowthami Somepalli Micah Goldblum Avi Schwarzschild C. Bayan Bruss Tom Goldstein LMTD 85 324 0 02 Jun 2021
Representing Numbers in NLP: a Survey and a Vision Avijit Thawani Jay Pujara Pedro A. Szekely Filip Ilievski 68 117 0 24 Mar 2021
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models Ahmed Alaa B. V. Breugel Evgeny S. Saveliev M. Schaar 85 193 0 17 Feb 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings Xin Huang A. Khetan Milan Cvitkovic Zohar Karnin ViT LMTD 195 447 0 11 Dec 2020
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 283 300 0 17 Mar 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 539 4,773 0 23 Jan 2020
Learning Numeral Embeddings Chengyue Jiang Zhonglin Nian Kaihao Guo Shanbo Chu Yinggong Zhao Libin Shen Kewei Tu 39 21 0 28 Dec 2019
Effectively Unbiased FID and Inception Score and where to find them Min Jin Chong David A. Forsyth EGVM 60 203 0 16 Nov 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 213 3,870 0 12 Jul 2019
Improved Precision and Recall Metric for Assessing Generative Models Tuomas Kynkaanniemi Tero Karras S. Laine J. Lehtinen Timo Aila EGVM 95 858 0 15 Apr 2019
Learning from Synthetic Data for Crowd Counting in the Wild Qi. Wang Junyu Gao Wei Lin Yuan. Yuan 79 527 0 08 Mar 2019
Assessing Generative Models via Precision and Recall Mehdi S. M. Sajjadi Olivier Bachem Mario Lucic Olivier Bousquet Sylvain Gelly EGVM 73 575 0 31 May 2018
Numeracy for Language Models: Evaluating and Improving their Ability to Predict Numbers Georgios P. Spithourakis Sebastian Riedel 51 83 0 21 May 2018