TL;DR
Results show that combining retrieval grounding with explainable and interactive mechanisms improves first-session recommendation quality and user transparency, and design insights for human-centred recommendation in semantically rich, behaviourally sparse settings.
NEO is introduced, a framework that adapts a pre-trained decoder-only LLM into a tool-free, catalog-grounded generator and treats SIDs as a distinct modality and study design choices for integrating discrete entity representations into LLMs via staged alignment and instruction tuning.
This method facilitates comprehensible recommendations via concept level reasoning pathway and realizes substantial enhancements in recommendation quality and user experience during the pivotal cold start phase and illustrates that ontological reasoning and hyperbolic geometry can mitigate essential cold start challeng...
In the proposed model, SBERT embeddings and FAISS indexing are used for effective semantic retrieval and hybrid ranking and explainability component is included in the architecture to provide explanations using similarity score, rating, popularity, author similarity and publication era.
This work introduces rubric-based preference reasoning, which uses automated rubrics to guide the model toward producing explicit preference states, and proposes a preference-conditioned optimization to align response generation with dual objectives: user preference satisfaction and situation consistency.
RecGPT is a fully integrated, production-ready framework that places user intent at the center of the recommendation pipeline by integrating large language models (LLMs) into key stages of user interest mining, item retrieval, and explanation generation, and transforms log-fitting recommendation into an intent-centric...
GARDRec, a Graph-grounded Adaptive Reasoning and Decision-aware Recommendation framework for LLM-based next-item ranking, is proposed, which improves candidate-ranking performance over representative baselines and verifies the contributions of graph projection, neighborhood retrieval, explicit decision features, rankin...
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