Transformers for tabular data representation: A survey of models and applications

G Badaro, M Saeed, P Papotti - Transactions of the Association for …, 2023 - direct.mit.edu
In the last few years, the natural language processing community has witnessed advances
in neural representations of free texts with transformer-based language models (LMs). Given …

Large language models for tabular data: Progresses and future directions

H Dong, Z Wang - Proceedings of the 47th International ACM SIGIR …, 2024 - dl.acm.org
Tables contain a significant portion of the world's structured information. The ability to
efficiently and accurately understand, process, reason about, analyze, and generate tabular …

Is table retrieval a solved problem? exploring join-aware multi-table retrieval

PB Chen, Y Zhang, D Roth - … of the 62nd Annual Meeting of the …, 2024 - aclanthology.org
Retrieving relevant tables containing the necessary information to accurately answer a given
question over tables is critical to open-domain question-answering (QA) systems. Previous …

Observatory: Characterizing embeddings of relational tables

T Cong, M Hulsebos, Z Sun, P Groth… - arxiv preprint arxiv …, 2023 - arxiv.org
Language models and specialized table embedding models have recently demonstrated
strong performance on many tasks over tabular data. Researchers and practitioners are …

Open-WikiTable: Dataset for open domain question answering with complex reasoning over table

S Kweon, Y Kwon, S Cho, Y Jo, E Choi - arxiv preprint arxiv:2305.07288, 2023 - arxiv.org
Despite recent interest in open domain question answering (ODQA) over tables, many
studies still rely on datasets that are not truly optimal for the task with respect to utilizing …

Database-Augmented Query Representation for Information Retrieval

S Jeong, J Baek, S Cho, SJ Hwang, JC Park - arxiv preprint arxiv …, 2024 - arxiv.org
Information retrieval models that aim to search for the documents relevant to the given query
have shown many successes, which have been applied to diverse tasks. However, the …

Bridging the gap between text-to-SQL research and real-world applications: A unified all-in-one framework for text-to-SQL

M Han, S Park, S Kim, H Kim - Knowledge-Based Systems, 2024 - Elsevier
Existing text-to-SQL research assumes the availability of gold table when generating SQL
queries. It is possible to effectively generate complex and difficult queries by leveraging …

OpenTab: Advancing large language models as open-domain table reasoners

K Kong, J Zhang, Z Shen, B Srinivasan, C Lei… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) trained on large volumes of data excel at various natural
language tasks, but they cannot handle tasks requiring knowledge that has not been trained …

Rb-sql: A retrieval-based llm framework for text-to-sql

Z Wu, Z Li, J Zhang, M Li, Y Zhao, R Fang, Z He… - arxiv preprint arxiv …, 2024 - arxiv.org
Large language models (LLMs) with in-context learning have significantly improved the
performance of text-to-SQL task. Previous works generally focus on using exclusive SQL …

Beyond Text-to-SQL for IoT Defense: A Comprehensive Framework for Querying and Classifying IoT Threats

R Pavlich, N Ebadi, R Tarbell, B Linares, A Tan… - arxiv preprint arxiv …, 2024 - arxiv.org
Recognizing the promise of natural language interfaces to databases, prior studies have
emphasized the development of text-to-SQL systems. While substantial progress has been …