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} }