3 papers
cs.CL2026
Intent-Driven Semantic ID Generation for Grounded Conversational News Recommendation
Hongyang Su, Beibei Kong, Lei Cheng +3
Conversational news recommendation requires grounding each suggestion in a rapidly evolving article corpus while addressing implicit user intents that lack explicit retrievable key…
cs.IR2026
SAGER: Self-Evolving User Policy Skills for Recommendation Agent
Zhen Tao, Riwei Lai, Chenyun Yu +7
Large language model (LLM) based recommendation agents personalize what they know through evolving per-user semantic memory, yet how they reason remains a universal, static system…
cs.MM2025
VRAgent-R1: Boosting Video Recommendation with MLLM-based Agents via Reinforcement Learning
Siran Chen, Boyu Chen, Chenyun Yu +6
Owing to powerful natural language processing and generative capabilities, large language model (LLM) agents have emerged as a promising solution for enhancing recommendation syste…