Deployed as a new retrieval source in the DPA production stack, SetMIR lifts overall CVR by 3.1%, while lifting CTR by 44% and CVR by 51% over the item-to-item retrieval source with the same item embeddings, ANN index, and retrieval quota.
Xiao-Dong Liu, Cong-Fei Zhang, Hsiang-Wei Chao et al.· 0 citations
Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally make in practice. Real-world requests are often open-ended, casually specified, and context-dependent, requiring models not only to follow explicit instructions but als...
Yong Peng, Qing-Shui Gu, Li-Ya Zhu et al.· 0 citations
This work systematically study AI products with demonstrated adoption, together with their product workflows and users, to identify real-world tasks for which AI has established practical demand across diverse professional domains and establishes StartupBench as an empirical measure of progress toward E2E completions o...
Li-Ya Zhu, Xin Ma, Tao Liu et al.· 1 citation
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