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cs.AI2025
Understanding Generative Recommendation with Semantic IDs from a Model-scaling View
Jingzhe Liu, Liam Collins, Jiliang Tang +3
Recent advancements in generative models have allowed the emergence of a promising paradigm for recommender systems (RS), known as Generative Recommendation (GR), which tries to un…
cs.CL2025
Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
Hang Li, Kaiqi Yang, Yucheng Chu +2
Large language models (LLMs) have been widely used for problem-solving tasks. Most recent work improves their performance through supervised fine-tuning (SFT) with labeled data or…