Xingrui Yu

Orcid: 0000-0002-8941-2698

According to our database¹, Xingrui Yu authored at least 33 papers between 2017 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

On csauthors.net:

Bibliography

2026

HBVLA: Pushing 1-Bit Post-Training Quantization for Vision-Language-Action Models.

[BibT_eX]

[DOI]

CoRR, February, 2026

Advancing Analytic Class-Incremental Learning through Vision-Language Calibration.

[BibT_eX]

[DOI]

CoRR, February, 2026

Mitigating Mismatch within Reference-based Preference Optimization.

[BibT_eX]

[DOI]

CoRR, February, 2026

SA-VLA: Spatially-Aware Flow-Matching for Vision-Language-Action Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, February, 2026

Time-Annealed Perturbation Sampling: Diverse Generation for Diffusion Language Models.

[BibT_eX]

[DOI]

CoRR, January, 2026

2025

Reflection-Driven Control for Trustworthy Code Agents.

[BibT_eX]

[DOI]

CoRR, December, 2025

GoRL: An Algorithm-Agnostic Framework for Online Reinforcement Learning with Generative Policies.

[BibT_eX]

[DOI]

CoRR, December, 2025

FM-IRL: Flow-Matching for Reward Modeling and Policy Regularization in Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, October, 2025

OSCAR: Orthogonal Stochastic Control for Alignment-Respecting Diversity in Flow Matching.

[BibT_eX]

[DOI]

CoRR, October, 2025

Self-Adaptive Gamma Context-Aware SSM-based Model for Metal Defect Detection.

[BibT_eX]

[DOI]

CoRR, March, 2025

Graph Potential Field Neural Network for Massive Agents Group-wise Path Planning.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2025

HREB-CRF: Hierarchical Reduced-bias EMA for Chinese Named Entity Recognition.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2025

Self-Adaptive Gamma Context-Aware SSM-based Model for Metal Defect Detection.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2025

Imitation from Diverse Behaviors: Wasserstein Quality Diversity Imitation Learning with Single-Step Archive Exploration.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

POI Recommendation via Multi-Objective Adversarial Imitation Learning.

[BibT_eX]

[DOI]

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

2024

USN: A Robust Imitation Learning Method against Diverse Action Noise.

[BibT_eX]

[DOI]

Xingrui Yu

Bo Han

Ivor W. Tsang

J. Artif. Intell. Res., 2024

Quality Diversity Imitation Learning.

[BibT_eX]

[DOI]

CoRR, 2024

A Comparative Study of Reinforcement Learning-based Collision Avoidance for Maritime Autonomous Surface Ships.

[BibT_eX]

[DOI]

Liangbin Zhao

Xingrui Yu

Xiuju Fu

Proceedings of the IEEE Conference on Artificial Intelligence, 2024

Fine-Grained Partial Label Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Artificial Intelligence, 2024

2020

Intrinsic Reward Driven Imitation Learning via Generative Model.

[BibT_eX]

[DOI]

Xingrui Yu

Yueming Lyu

Ivor W. Tsang

Proceedings of the 37th International Conference on Machine Learning, 2020

SIGUA: Forgetting May Make Learning with Noisy Labels More Robust.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Deep Adversarial Learning in Intrusion Detection: A Data Augmentation Enhanced Framework.

[BibT_eX]

[DOI]

CoRR, 2019

How does Disagreement Help Generalization against Label Corruption?

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Oil Spill Segmentation via Adversarial f-Divergence Learning.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2018

Stereo Matching via Dual Fusion.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2018

Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels.

[BibT_eX]

[DOI]

CoRR, 2018

Co-sampling: Training Robust Networks for Extremely Noisy Supervision.

[BibT_eX]

[DOI]

CoRR, 2018

Co-teaching: Robust training of deep neural networks with extremely noisy labels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Typhoon Cloud Prediction Via Generative Adversarial Networks.

[BibT_eX]

[DOI]

Hui Li

Xingrui Yu

Peng Ren

Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017

Level sets with self-guided filtering for marine oil spill segmentation.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

MCMC Based Generative Adversarial Networks for Handwritten Numeral Augmentation.

[BibT_eX]

[DOI]

Proceedings of the Communications, Signal Processing, and Systems, 2017

Xingrui Yu

Timeline

Legend:

Links

On csauthors.net:

Bibliography

Loading...