2 papers
cs.AI2026
Adaptive Semantic Capacity Allocation for Parallel Generative Recommendation
Chenxi Li, Yuchen Lu, Xu Yang
Autoregressive semantic ID recommenders are constrained by expensive beam-search decoding, which limits the practical length of item identifiers. Parallel generation methods allevi…
cs.IR2026
An LLM-powered Agentic Recommendation System for Connected TV Content Discovery
Lei Shi, Di Wang, Harry Tran +22
Recommendation systems, from traditional multi-stage to recent unified generative architectures, face challenges in incorporating diverse contextual signals, such as trending topic…