Beyond Sequences: Distilling Structured Decision Memory for LLM Recommendation
Despite the adoption of large language models (LLMs) in recommendation systems, prevailing approaches mostly model single-type behaviors (e.g., views or purchases). Even when incorporating multiple behaviors, existing methods flatten heterogeneous actions into homogeneous token sequences, ignoring their distinct decisi...
Lei Liang, Guo-Shuai Wang, Xin He et al.
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