We stand with Ukraine

We stand with Ukraine

Beibei Li

Orcid: 0000-0003-2711-9370

Affiliations:

Institute of Software, Chinese Academy of Sciences, Beijing, China

According to our database¹, Beibei Li authored at least 29 papers between 2019 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

Online presence:

on orcid.org

On csauthors.net:

Bibliography

2026

Look Closer! An Adversarial Parametric Editing Framework for Hallucination Mitigation in VLMs.

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Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Corrigendum: An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes.

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ACM Trans. Intell. Syst. Technol., December, 2025

AsyCo: an asymmetric dual-task co-training model for partial-label learning.

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Sci. China Inf. Sci., 2025

Collaborative Interest-Aware Graph Learning for Group Identification.

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Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track and Demo Track, 2025

Semantic Gaussian Mixture Variational Autoencoder for Sequential Recommendation.

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Proceedings of the Database Systems for Advanced Applications, 2025

2024

Multiple-Instance Learning from Pairwise Comparison Bags.

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ACM Trans. Intell. Syst. Technol., December, 2024

An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes.

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ACM Trans. Intell. Syst. Technol., December, 2024

Denoising Long- and Short-term Interests for Sequential Recommendation.

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Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Multi-intent Driven Contrastive Sequential Recommendation.

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Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

Orthogonal Hyper-category Guided Multi-interest Elicitation for Micro-video Matching.

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Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Enhancing Sequential Recommendation via Aligning Interest Distributions.

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Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

Reducing Interaction Noise for Sequential Recommendation via Robust Interests.

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Proceedings of the Database Systems for Advanced Applications, 2024

2023

A Vlogger-augmented Graph Neural Network Model for Micro-video Recommendation.

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Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

Gemini: A Dual-Task Co-training Model for Partial Label Learning.

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Proceedings of the AI 2023: Advances in Artificial Intelligence, 2023

2022

Improving Micro-video Recommendation via Contrastive Multiple Interests.

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CoRR, 2022

Modeling user interactions by feature-augmented graph neural networks for recommendation.

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CCF Trans. Pervasive Comput. Interact., 2022

Denoising Sequence Embeddings via Contrastive Learning for Micro-video Recommendation.

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Proceedings of the IEEE Smartworld, 2022

Improving Micro-video Recommendation via Contrastive Multiple Interests.

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Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Improving Micro-video Recommendation by Controlling Position Bias.

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Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

MARS: A Multi-task Ranking Model for Recommending Micro-videos.

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Proceedings of the Web and Big Data - 6th International Joint Conference, 2022

2021

MULTIPLE: Multi-level User Preference Learning for List Recommendation.

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Proceedings of the Web Information Systems Engineering - WISE 2021, 2021

Improving Sequential Recommendation with Attribute-Augmented Graph Neural Networks.

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Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

List Recommendation via Co-attentive User Preference Fine-Tuning.

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Proceedings of the Neural Information Processing - 28th International Conference, 2021

Sirius: Sequential Recommendation with Feature Augmented Graph Neural Networks.

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Proceedings of the Database Systems for Advanced Applications, 2021

A Behavior-Aware Graph Convolution Network Model for Video Recommendation.

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Proceedings of the Web and Big Data - 5th International Joint Conference, 2021

2020

Feedback-Guided Attributed Graph Embedding for Relevant Video Recommendation.

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Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

2019

Cold-Start Recommendation for On-Demand Cinemas.

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Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Spatial-Temporal Recommendation for On-demand Cinemas.

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Proceedings of the Database Systems for Advanced Applications, 2019

A Spatio-temporal Recommender System for On-demand Cinemas.

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Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

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