2 papers
cs.AI2026
Boosting Knowledge Graph Foundation Models via Enhanced Negative Sampling
Yinan Liu, Wenjin Xu, Zhiyuan Zha +2
Knowledge graphs (KGs) have become the core backbone of numerous downstream tasks such as question answering and recommender systems. However, despite all this, KGs are often very…
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…