RESEARCH

NLP

TaBert: Pretraining for Joint Understanding of Textual and Tabular Data

May 06, 2020

Abstract

Recent years have witnessed the burgeoning of pretrained language models (LMs) for text-based natural language (NL) understanding tasks. Such models are typically trained on free-form NL text, hence may not be suitable for tasks like semantic parsing over structured data, which require reasoning over both free-form NL questions and structured tabular data (e.g., database tables). In this paper we present TABERT, a pretrained LM that jointly learns representations for NL sentences and (semi-)structured tables. TaBert is trained on a large corpus of 26 million tables and their English contexts. In experiments, neural semantic parsers using TABERT as feature representation layers achieve new best results on the challenging weakly-supervised semantic parsing benchmark WikiTableQuestions, while performing competitively on the text-to-SQL dataset Spider.

Download the Paper

AUTHORS

Written by

Scott Yih

Sebastian Riedel

Graham Neubig

Pengcheng Yin

Publisher

ACL

Related Publications

December 07, 2023

CONVERSATIONAL AI

NLP

Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Hakan Inan, Kartikeya Upasani, Jianfeng Chi, Rashi Rungta, Krithika Iyer, Yuning Mao, Davide Testuggine, Madian Khabsa

December 07, 2023

December 06, 2023

NLP

Polar Ducks and Where to Find Them: Enhancing Entity Linking with Duck Typing and Polar Box Embeddings

Mattia Atzeni, Mike Plekhanov, Frederic Dreyer, Nora Kassner, Simone Merello, Louis Martin, Nicola Cancedda

December 06, 2023

December 04, 2023

NLP

PATHFINDER: Guided Search over Multi-Step Reasoning Paths

Olga Golovneva, Sean O'Brien, Ram Pasunuru, Tianlu Wang, Luke Zettlemoyer, Maryam Fazel-Zarandi, Asli Celikyilmaz

December 04, 2023

November 30, 2023

SPEECH & AUDIO

NLP

Efficient Monotonic Multihead Attention

Xutai Ma, Anna Sun, Siqi Ouyang, Hirofumi Inaguma, Paden Tomasello

November 30, 2023

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.