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cs.IR2026
RankEvolve: Automating the Discovery of Retrieval Algorithms via LLM-Driven Evolution
Jinming Nian, Fangchen Li, Dae Hoon Park +1
Retrieval algorithms like BM25 and query likelihood with Dirichlet smoothing remain strong and efficient first-stage rankers, yet improvements have mostly relied on parameter tunin…
cs.IR2026
Towards Sample-Efficient and Stable Reinforcement Learning for LLM-based Recommendation
Hongxun Ding, Keqin Bao, Jizhi Zhang +4
While Long Chain-of-Thought (Long CoT) reasoning has shown promise in Large Language Models (LLMs), its adoption for enhancing recommendation quality is growing rapidly. In this wo…