Papers by Changyi Ma

1 papers
C2KD: Cross-layer and Cross-head Knowledge Distillation for Small Language Model-based Recommendation (2025.findings-acl)

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Challenge: Large Language Models (LLMs) show promise but their size and high inference costs limit deployment on resource-constrained devices.
Approach: They propose a framework to transfer task-relevant knowledge from two complementary dimensions to Large Language Models (LLMs) Large Language models (LLMS) have demonstrated great potential in sequential recommendation tasks .
Outcome: Extensive experiments across diverse model families show that the proposed framework achieves competitive performance compared to LLMs.

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