Corpus-Centric Learning for Zero-Shot Table Retrieval
GeCo-TR is proposed, a zero-shot table retrieval framework that eliminates the need for supervised QA data by shifting from direct query-to-table learning to modeling the intrinsic structural semantics of the table corpus, resulting in high-precision and high-recall retrieval for implicit queries in a zero-shot setting.