3 papers
cs.CL2026
MemRerank: Preference Memory for Personalized Product Reranking
Zhiyuan Peng, Xuyang Wu, Huaixiao Tou +2
LLM-based shopping agents increasingly rely on long purchase histories and multi-turn interactions for personalization, yet naively appending raw history to prompts is often ineffe…
math.OC2026
An Accelerated Proximal Bundle Method with Momentum
Zhuoqing Zheng, Junshan Yin, Shaofu Yang +1
Proximal bundle methods (PBM) are a powerful class of algorithms for convex optimization. Compared to gradient descent, PBM constructs more accurate surrogate models that incorpora…
math.OC2026
Bundle EXTRA for Decentralized Optimization
Haijuan Liu, Zhuoqing Zheng, Cong Li +2
Decentralized primal-dual methods are widely used for solving decentralized optimization problems, but their updates often rely on the potentially crude first-order Taylor approxim…