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
This work proposes ToolSearcher, a novel RL framework for effective multi-turn search and fine-grained optimization in large-scale tool selection, which introduces category-constrained tool discrimination to improve the model's ability to distinguish functionally similar tools.
Zhen-Long Dai, Xu-Jie Song, Zi-Tong Wang 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
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
