Why Tabular Foundation Models Should Be a Research Priority

2 May 2024

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

8 / 8 papers shown

Title
Generative Calibration for In-context Learning Zhongtao Jiang Yuanzhe Zhang Cao Liu Jun Zhao Kang Liu 147 8 0 16 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 62 20 0 11 Oct 2023
Multimodal Foundation Models: From Specialists to General-Purpose Assistants Chunyuan Li Zhe Gan Zhengyuan Yang Jianwei Yang Linjie Li Lijuan Wang Jianfeng Gao MLLM 107 221 0 18 Sep 2023
Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources Xingxuan Li Ruochen Zhao Yew Ken Chia Bosheng Ding Shafiq R. Joty Soujanya Poria Lidong Bing HILM BDL LRM 77 85 0 22 May 2023
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 36 135 0 17 Feb 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings Xin Huang A. Khetan Milan Cvitkovic Zohar S. Karnin ViT LMTD 138 412 0 11 Dec 2020
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 229 288 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 220 3,054 0 23 Jan 2020