Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study.
Yuan Sui|Mengyu Zhou|Mingjie Zhou|Shi Han|Dongmei Zhang
| Anthology ID: | DBLP:conf/wsdm/SuiZZH024 |
|---|---|
| Volume: | Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024 |
| Year: | 2024 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 645-654 |
| URL: | https://doi.org/10.1145/3616855.3635752 |
| DOI: | https://doi.org/10.1145/3616855.3635752 |
| DBLP: | conf/wsdm/SuiZZH024 |
| BibTeX: |
@inproceedings{sui-2024-table,
author = {Yuan Sui and
Mengyu Zhou and
Mingjie Zhou and
Shi Han and
Dongmei Zhang},
editor = {Luz Angelica Caudillo-Mata and
Silvio Lattanzi and
Andr\'{e}s Mu\~{n}oz Medina and
Leman Akoglu and
Aristides Gionis and
Sergei Vassilvitskii},
title = {{Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study}},
booktitle = {{Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024}},
pages = {645--654},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3616855.3635752},
doi = {https://doi.org/10.1145/3616855.3635752}
}