3 papers
cs.IR2026
From Item-Only to Query-Item: Query-Conditioned Generative Search with QGS in Quark
Yanglong Song, Zihao Yang, Shuo Meng +6
Generative sequence models have shown strong results in recommendation. Applying them to search ranking is more challenging. Search behavior is inherently query-driven. Each query…
cs.IR2026
Learning Deep Tree-based Retriever for Efficient Recommendation: Theory and Method
Ze Liu, Jin Zhang, Chao Feng +3
Although advancements in deep learning have significantly enhanced the recommendation accuracy of deep recommendation models, these methods still suffer from low recommendation eff…
cs.LG2025
Adaptive Sampled Softmax with Inverted Multi-Index: Methods, Theory and Applications
Jin Chen, Jin Zhang, Xu huang +3
The softmax function is a cornerstone of multi-class classification, integral to a wide range of machine learning applications, from large-scale retrieval and ranking models to adv…