Futa Waseda

Orcid: 0009-0004-5902-1567

According to our database1, Futa Waseda authored at least 15 papers between 2023 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Multimodal Adversarial Defense for Vision-Language Models by Leveraging One-To-Many Relationships.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2026

2025
Read or Ignore? A Unified Benchmark for Typographic-Attack Robustness and Text Recognition in Vision-Language Models.
CoRR, December, 2025

Text-Printed Image: Bridging the Image-Text Modality Gap for Text-centric Training of Large Vision-Language Models.
CoRR, December, 2025

Understanding Sensitivity of Differential Attention through the Lens of Adversarial Robustness.
CoRR, October, 2025

Quality Text, Robust Vision: The Role of Language in Enhancing Visual Robustness of Vision-Language Models.
Proceedings of the 33rd ACM International Conference on Multimedia, 2025

Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Allegory of the Cave: Breakdown of Illusions in Multimodal Perception with Neural Radiance Fields.
Proceedings of the Asia Pacific Signal and Information Processing Association Annual Summit and Conference, 2025

Uncolorable Examples: Preventing Unauthorized AI Colorization via Perception-Aware Chroma-Restrictive Perturbation.
Proceedings of the Asia Pacific Signal and Information Processing Association Annual Summit and Conference, 2025

MergePrint: Merge-Resistant Fingerprints for Robust Black-box Ownership Verification of Large Language Models.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
MergePrint: Robust Fingerprinting against Merging Large Language Models.
CoRR, 2024

Leveraging Many-To-Many Relationships for Defending Against Visual-Language Adversarial Attacks.
CoRR, 2024

Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off.
CoRR, 2024

Defending Against Physical Adversarial Patch attacks On Infrared Human Detection.
Proceedings of the IEEE International Conference on Image Processing, 2024

2023
Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Beyond In-Domain Scenarios: Robust Density-Aware Calibration.
Proceedings of the International Conference on Machine Learning, 2023


  Loading...