Large language models are reshaping ecommerce from static recommenders into interactive shopping assistants, yet real-world shopping requires session-level decision support: users reveal and revise constraints, coordinate multiple goals, and expect product-grounded recommendations over a full conversation. Existing ben...
Xin-Wei Yang, Ke-Long Mao, Yu-Dong Guo et al.· 0 citations
T cell receptor (TCR) recognition prediction and receptor generation are traditionally modelled separately, leaving vast TCR sequence collections disconnected from smaller TCR–peptide–MHC datasets. Here we present OmniTCR, a 113-million-parameter autoregressive foundation model pretrained on 328 million formatted human...
Fei-Ran Zeng, Duanyu Feng, Dan-Dan Song et al.· bioRxiv· 0 citations
DREAMS is proposed, a novel tree-structured context modeling framework that explicitly captures user preference evolution throughout multi-turn interactions and introduces two specialized node types to support the two fundamental objectives of CRSs: preference elicitation and preference exploitation.
Jin-Cheng Zhang, Chen Huang, Wen-Qiang Lei et al.· 0 citations
It is argued that missing spatial constraints should be inferred with respect to the underlying construction structure and informed by reusable design experience and informed by reusable design experience in ExpConCAD, an experience-enhanced framework for implicit spatial constraint completion.
Jingyao Liu, Jin Tang, Chen Huang et al.· 0 citations
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