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Zaifu Zhan

2 accepted papers

2025

The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit

ACL 2025long

The deployment of Large Language Models (LLMs) in recommender systems for Click-Through Rate (CTR) prediction requires a careful balance between computational efficiency and predictive accuracy. This paper introduces OptiRAG-Rec, a comprehensive framework that integrates Retrieval-Augmented Generati…

Cited by 0SourcePDFScholar
2025

Towards Better Multi-task Learning: A Framework for Optimizing Dataset Combinations in Large Language Models

NAACL 2025findings

To efficiently select optimal dataset combinations for enhancing multi-task learning (MTL) performance in large language models, we proposed a novel framework that leverages a neural network to predict the best dataset combinations. The framework iteratively refines the selection, greatly improving…