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Atsuyuki Miyai
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2020 – today
- 2024
- [j1]Kazuki Egashira, Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa:
Negative Learning to Prevent Undesirable Misclassification. IEICE Trans. Inf. Syst. 107(1): 144-147 (2024) - [i7]Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Qing Yu, Go Irie, Yixuan Li, Hai Li, Ziwei Liu, Kiyoharu Aizawa:
Unsolvable Problem Detection: Evaluating Trustworthiness of Vision Language Models. CoRR abs/2403.20331 (2024) - [i6]Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Yueqian Lin, Qing Yu, Go Irie, Shafiq Joty, Yixuan Li, Hai Li, Ziwei Liu, Toshihiko Yamasaki, Kiyoharu Aizawa:
Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey. CoRR abs/2407.21794 (2024) - [i5]Shota Onohara, Atsuyuki Miyai, Yuki Imajuku, Kazuki Egashira, Jeonghun Baek, Xiang Yue, Graham Neubig, Kiyoharu Aizawa:
JMMMU: A Japanese Massive Multi-discipline Multimodal Understanding Benchmark for Culture-aware Evaluation. CoRR abs/2410.17250 (2024) - 2023
- [c2]Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa:
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning. NeurIPS 2023 - [c1]Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa:
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation. WACV 2023: 2808-2817 - [i4]Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa:
Zero-Shot In-Distribution Detection in Multi-Object Settings Using Vision-Language Foundation Models. CoRR abs/2304.04521 (2023) - [i3]Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa:
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning. CoRR abs/2306.01293 (2023) - [i2]Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa:
Can Pre-trained Networks Detect Familiar Out-of-Distribution Data? CoRR abs/2310.00847 (2023) - 2022
- [i1]Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa:
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation. CoRR abs/2210.12681 (2022)
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