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- research-articleOctober 2024
MMLRec: A Unified Multi-Task and Multi-Scenario Learning Benchmark for Recommendation
- Guanghu Yuan,
- Jieyu Yang,
- Shujie Li,
- Mingjie Zhong,
- Ang Li,
- Ke Ding,
- Yong He,
- Min Yang,
- Liang Zhang,
- Xiaolu Zhang,
- Linjian Mo
CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge ManagementPages 3063–3072https://doi.org/10.1145/3627673.3679691In recent years, there has been a trend in the field of recommender systems towards multi-task modeling and multi-scenario modeling. The aim is to enhance the performance of various tasks and scenarios by jointly training on multiple tasks or scenarios ...
- research-articleOctober 2024
Bridge the Gap between Past and Future: Siamese Model Optimization for Context-Aware Document Ranking
CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge ManagementPages 2564–2574https://doi.org/10.1145/3627673.3679661In the realm of information retrieval, users often engage in multi-turn interactions with search engines to acquire information, leading to the formation of sequences of user feedback behaviors. Leveraging the session context has proven to be beneficial ...