Capturing user preference from a user's interaction sequence is the central challenge of Sequential Recommendation (SR). This preference intuitively emerges from inter-item relations: each item transition reflects a preference embedded in the relations between items, making the faithful capture of these relations essen...
Junyoung Kim, Wonbin Kweon, Woojoo Kim et al.· 2 citations
Across three models, two reasoning regimes, and two domains, four findings hold without per-turn reasoning: displaying accurate state is unreliable, an unverified ledger the agent writes itself beats an accurate checklist it is shown, directives help in proportion to the model's obedience, and enforcement needs no obed...
Recommendation systems increasingly adopt a two-stage pipeline, where an ID-based retriever retrieves candidates and an LLM-based reranker refines their rankings. To improve retrieval quality, reranker-to-retriever distillation is commonly used to transfer the reranker's knowledge to the retriever. For practical deploy...
S. Baek, Gyuseok Lee, Seunghan Lee et al.· 0 citations
This tutorial presents a unified vision in which structuring serves as the enabling foundation for three pillars of next-generation LLM systems, highlighting how the cooperative interplay between classical KDD techniques and modern LLMs-where KDD defines structural schemas and quality constraints while LLMs execute fle...
Peng-Cheng Jiang, Jiashuo Sun, Wonbin Kweon et al.· Proceedings of the 32nd ACM...· 0 citations
A model-agnostic framework that forms personalized item embeddings through Long-Horizon Local Optimization and injects common global knowledge through intermittent Regularized Knowledge Guidance is proposed and Adaptive Guidance is introduced to control the influence of global knowledge at the user–item interaction lev...
Jaehyung Lim, Wonbin Kweon, Woojoo Kim et al.· Journal of Intelligence and...· 0 citations
This tutorial presents a unified vision in which structuring serves as the enabling foundation for three pillars of next-generation LLM systems, highlighting how the cooperative interplay between classical KDD techniques and modern LLMs-where KDD defines structural schemas and quality constraints while LLMs execute fle...
Pengcheng Jiang, Jiashuo Sun, Wonbin Kweon et al.· Proceedings of the 32nd ACM...· 0 citations
PMFRec learns a personalized representation generator to produce user-specific item representations from attribute features, and introduces a global multi-view encoder with item-adaptive gating and an orthogonality objective to capture complementary semantic views while reducing cross-view redundancy.
Jaehyung Lim, Wonbin Kweon, Woojoo Kim et al.· 0 citations
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