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cs.LG2026
Goal-Conditioned Supervised Learning for LLM Fine-Tuning
Shijun Li, Kaiwen Dong, Xiang Gao +1
Large language models often require fine-tuning to better align their behavior with user intent at deployment. Existing approaches are commonly divided into online and offline para…
cs.IR2026
RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation
Shijun Li, Wooseong Yang, Pranav Belligundu +3
Large Language Models (LLMs) have emerged as a promising paradigm for next-generation recommender systems, offering strong semantic understanding and natural-language reasoning abi…