3 papers
cs.IR2025
Diversity Recommendation via Causal Deconfounding of Co-purchase Relations and Counterfactual Exposure
Jingmao Zhang, Zhiting Zhao, Yunqi Lin +4
Beyond user-item modeling, item-to-item relationships are increasingly used to enhance recommendation. However, common methods largely rely on co-occurrence, making them prone to i…
cs.CV2025
Uncovering Intrinsic Capabilities: A Paradigm for Data Curation in Vision-Language Models
Junjie Li, Ziao Wang, Jianghong Ma +1
Large vision-language models (VLMs) achieve strong benchmark performance, but controlling their behavior through instruction tuning remains difficult. Reducing the budget of instru…
cs.IR2025
Dual-Phase Playtime-guided Recommendation: Interest Intensity Exploration and Multimodal Random Walks
Jingmao Zhang, Zhiting Zhao, Yunqi Lin +4
The explosive growth of the video game industry has created an urgent need for recommendation systems that can scale with expanding catalogs and maintain user engagement. While pri…