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Qingyu Xiong

2 accepted papers

2024

Ranking Enhanced Fine-Grained Contrastive Learning for Recommendation

ICASSP 2024accepted

Contrastive learning (CL) has been widely used to improve recommendation performance, since its self-supervised signals can effectively alleviate the data sparsity issue in recommender systems. Nevertheless, most existing CL-based recommendation models construct negative sample pairs following the c…

Cited by 0SourceScholar
2022

Prior-Bert and Multi-Task Learning for Target-Aspect-Sentiment Joint Detection

ICASSP 2022accepted

Aspect-Based Sentiment Analysis (ABSA) is a fine-grained sentiment analysis task and has become a significant task with real-world scenario value. The challenge of this task is how to generate an effective text representation and construct an end-to-end model that can simultaneously detect (target,…

Cited by 0SourceScholar