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cs.IR2023
Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation
Bo Peng, Ben Burns, Ziqi Chen +2
In recent years, with large language models (LLMs) achieving state-of-the-art performance in context understanding, increasing efforts have been dedicated to developing LLM-enhance…
cs.IR2023
Multi-modality Meets Re-learning: Mitigating Negative Transfer in Sequential Recommendation
Bo Peng, Srinivasan Parthasarathy, Xia Ning
Learning effective recommendation models from sparse user interactions represents a fundamental challenge in developing sequential recommendation methods. Recently, pre-training-ba…