Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders.
CoRR, March, 2025
Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation.
IEEE Trans. Knowl. Data Eng., January, 2025
Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025
Legommenders: A Comprehensive Content-Based Recommendation Library with LLM Support.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025
Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
NetSafe: Exploring the Topological Safety of Multi-agent Networks.
CoRR, 2024
STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLM.
CoRR, 2024
Structure-aware Semantic Node Identifiers for Learning on Graphs.
CoRR, 2024
Vector Quantization for Recommender Systems: A Review and Outlook.
CoRR, 2024
Benchmarking News Recommendation in the Era of Green AI.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024
Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization.
Proceedings of the ACM on Web Conference 2024, 2024
Discrete Semantic Tokenization for Deep CTR Prediction.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024
ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024
AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment.
Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, 2024
CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision.
Proceedings of the Advances in Information Retrieval, 2024
EasyGen: Easing Multimodal Generation with BiDiffuser and LLMs.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation.
CoRR, 2023
Making Multimodal Generation Easier: When Diffusion Models Meet LLMs.
CoRR, 2023
Dataset Condensation for Recommendation.
CoRR, 2023
Enhancing Graph Collaborative Filtering via Uniformly Co-Clustered Intent Modeling.
CoRR, 2023
Co-evolving Vector Quantization for ID-based Recommendation.
CoRR, 2023
Only Encode Once: Making Content-based News Recommender Greener.
CoRR, 2023
A First Look at LLM-Powered Generative News Recommendation.
CoRR, 2023
FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation.
Proceedings of the ACM Web Conference 2023, 2023
Continual Graph Convolutional Network for Text Classification.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation.
Proceedings of the 29th International Conference on Computational Linguistics, 2022
Weak Supervision Enhanced Generative Network for Question Generation.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019