Papers by Shijie Geng

2 papers
Improving Personalized Explanation Generation through Visualization (2022.acl-long)

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Challenge: Existing explainable recommendation models generate repetitive sentences for different items or empty sentences with insufficient details.
Approach: They propose a visual-enhanced approach to generate rating scores and text explanations using visualization generation and text–image matching discrimination.
Outcome: The proposed approach improves both the text quality and the diversity and explainability of the generated explanations.
VIP5: Towards Multimodal Foundation Models for Recommendation (2023.findings-emnlp)

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Challenge: Recent advances in foundation models have impeded the ability for these fields to benefit from each other’s advancements.
Approach: They propose to use a multimodal foundation model to unify various modalities and recommendation tasks under the P5 recommendation paradigm to implement personalized prompts.
Outcome: The proposed model will unify visual, textual, and personalization modalities under the P5 recommendation paradigm and will improve recommendation performance and efficiency.

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