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10 papers
Emotion and Intention Guided Multi-Modal Learning for Sticker Response Selection
Yuxuan Hu, Jian Chen, Yuhao Wang +6
Stickers are widely used in online communication to convey emotions and implicit intentions. The Sticker Response Selection (SRS) task aims to select the most contextually appropri…
Empowering Denoising Sequential Recommendation with Large Language Model Embeddings
Tongzhou Wu, Yuhao Wang, Maolin Wang +2
Sequential recommendation aims to capture user preferences by modeling sequential patterns in user-item interactions. However, these models are often influenced by noise such as ac…
Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs
Yuhao Wang, Junwei Pan, Xinhang Li +6
Sequential recommendation (SR) aims to capture users' dynamic interests and sequential patterns based on their historical interactions. Recently, the powerful capabilities of large…
ECKGBench: Benchmarking Large Language Models in E-commerce Leveraging Knowledge Graph
Langming Liu, Haibin Chen, Yuhao Wang +5
Large language models (LLMs) have demonstrated their capabilities across various NLP tasks. Their potential in e-commerce is also substantial, evidenced by practical implementation…
Joint Modeling in Recommendations: A Survey
Xiangyu Zhao, Yichao Wang, Bo Chen +7
In today's digital landscape, Deep Recommender Systems (DRS) play a crucial role in navigating and customizing online content for individual preferences. However, conventional meth…
Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark
Xiaopeng Li, Jingtong Gao, Pengyue Jia +7
Multi Scenario Recommendation (MSR) tasks, referring to building a unified model to enhance performance across all recommendation scenarios, have recently gained much attention. Ho…