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We stand with Ukraine

Yongxin Guo

Orcid: 0009-0001-8652-0722

Affiliations:

Chinese University of Hong Kong (Shenzhen), School of Science and Engineering, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China (PhD 2025)

According to our database¹, Yongxin Guo authored at least 28 papers between 2021 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 csauthors.net:

Bibliography

2026

Select Smarter, Not More: Prompt-Aware Evaluation Scheduling with Submodular Guarantees.

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CoRR, April, 2026

Structured Causal Video Reasoning via Multi-Objective Alignment.

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Mohammed Bennamoun

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Farid Boussaïd

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CoRR, April, 2026

PIDP-Attack: Combining Prompt Injection with Database Poisoning Attacks on Retrieval-Augmented Generation Systems.

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CoRR, March, 2026

Adaptive Prompt Structure Factorization: A Framework for Self-Discovering and Optimizing Compositional Prompt Programs.

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Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

G²RPO-A: Guided Group Relative Policy Optimization with Adaptive Guidance.

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Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

Multi-Physics: A Comprehensive Benchmark for Multimodal LLMs Reasoning on Chinese Multi-Subject Physics Problems.

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CoRR, September, 2025

Personalized Federated Management and Load Balancing for Multiple Charging Stations.

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IEEE Trans. Ind. Informatics, August, 2025

G<sup>2</sup>RPO-A: Guided Group Relative Policy Optimization with Adaptive Guidance.

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CoRR, August, 2025

Camouflaged Variational Graph AutoEncoder Against Attribute Inference Attacks for Cross-Domain Recommendation.

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IEEE Trans. Knowl. Data Eng., July, 2025

Watch and Listen: Understanding Audio-Visual-Speech Moments with Multimodal LLM.

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Mohammed Bennamoun

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Farid Boussaïd

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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Enhancing Long Video Understanding via Hierarchical Event-Based Memory.

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Proceedings of the IEEE International Conference on Multimedia and Expo, 2025

TRACE: Temporal Grounding Video LLM via Causal Event Modeling.

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Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models.

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Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies.

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Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing.

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Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding.

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Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Smart Sampling: Helping from Friendly Neighbors for Decentralized Federated Learning.

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CoRR, 2024

VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding.

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CoRR, 2024

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering.

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Proceedings of the Forty-first International Conference on Machine Learning, 2024

FedMABA: Towards Fair Federated Learning through Multi-Armed Bandits Allocation.

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Ying-Jun Angela Zhang

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Proceedings of the 24th IEEE International Conference on Communication Technology, 2024

2023

Find Your Optimal Assignments On-the-fly: A Holistic Framework for Clustered Federated Learning.

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CoRR, 2023

FedConceptEM: Robust Federated Learning Under Diverse Distribution Shifts.

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CoRR, 2023

PITPS: Balancing Local and Global Profits for Multiple Charging Stations Management.

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Proceedings of the IEEE International Conference on Communications, 2023

DELTA: Diverse Client Sampling for Fasting Federated Learning.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction.

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Proceedings of the International Conference on Machine Learning, 2023

2022

Client Selection in Nonconvex Federated Learning: Improved Convergence Analysis for Optimal Unbiased Sampling Strategy.

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CoRR, 2022

FedAug: Reducing the Local Learning Bias Improves Federated Learning on Heterogeneous Data.

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CoRR, 2022

2021

Towards Federated Learning on Time-Evolving Heterogeneous Data.

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CoRR, 2021

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