Develops COF algorithm for MAB-CS that intelligently checks cheap arm feasibility by pooling samples, with generalized instance-dependent lower bounds and matching upper bounds on cumulative cost and quality regret.
Item recommendation on monotonic behavior chains
3 Pith papers cite this work. Polarity classification is still indexing.
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RRCM trains an LLM to dynamically retrieve from collaborative and meta memories using group relative policy optimization driven by final top-k recommendation quality.
A simple graph heuristic without training or sequence encoders matches or outperforms trained generative recommenders on 10 of 14 sequential recommendation benchmarks by exploiting local transition and feature shortcuts.
citing papers explorer
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Cost-Ordered Feasibility for Multi-Armed Bandits with Cost Subsidy
Develops COF algorithm for MAB-CS that intelligently checks cheap arm feasibility by pooling samples, with generalized instance-dependent lower bounds and matching upper bounds on cumulative cost and quality regret.
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RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation
RRCM trains an LLM to dynamically retrieve from collaborative and meta memories using group relative policy optimization driven by final top-k recommendation quality.
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An Embarrassingly Simple Graph Heuristic Reveals Shortcut-Solvable Benchmarks for Sequential Recommendation
A simple graph heuristic without training or sequence encoders matches or outperforms trained generative recommenders on 10 of 14 sequential recommendation benchmarks by exploiting local transition and feature shortcuts.