Current text-based person retrieval (TBPR) systems are typically built on English-pretrained vision-language backbones and evaluated on English-only, single-domain benchmarks. This setting limits their applicability to multilingual queries and encourages reliance on dataset-specific shortcuts, resulting in weak cross-d...
Hao-Tian Yang, Cheng Peng, Hao-Bo Wang et al.· 0 citations
LLM-powered data analytics aims to translate natural language instructions into executable analytical programs over underlying data. However, existing approaches, whether treating LLMs as intent-to-code translators or as standalone analytical engines, often fail to reliably align domain semantics with complex schemas a...
Rui-Chen Xia, Xiao-Chuan Han, Ding-Yu Yang et al.· 0 citations
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...
Zhou He, Zhifei Pang, Xiu Tang et al.· Annual International ACM SIG...· 0 citations
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