Yuanqi Yao

Orcid: 0009-0005-3012-9395

According to our database1, Yuanqi Yao authored at least 16 papers between 2023 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2025
A visual-language foundation model for disease diagnosis and doctor-patient co-decision.
Vis. Comput., August, 2025

DSTS-GF: a dual-stream temporal-spatial transformer with gated fusion for the classification of Obstructive Sleep Apnea.
Vis. Comput., August, 2025

Probing the Robustness of Large Language Models Safety to Latent Perturbations.
CoRR, June, 2025

Hume: Introducing System-2 Thinking in Visual-Language-Action Model.
CoRR, May, 2025

Invisible Entropy: Towards Safe and Efficient Low-Entropy LLM Watermarking.
CoRR, May, 2025

Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation.
CoRR, April, 2025

FUSE: Label-Free Image-Event Joint Monocular Depth Estimation via Frequency-Decoupled Alignment and Degradation-Robust Fusion.
CoRR, March, 2025

SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model.
CoRR, January, 2025

Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

From Evasion to Concealment: Stealthy Knowledge Unlearning for LLMs.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
MEOW: MEMOry Supervised LLM Unlearning Via Inverted Facts.
CoRR, 2024

MLLMGuard: A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training.
Proceedings of the Computer Vision - ECCV 2024, 2024



2023
The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation.
CoRR, 2023


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