Ryotaro Shimizu

According to our database, Ryotaro Shimizu authored at least 26 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

DisTaC: Conditioning Task Vectors via Distillation for Robust Model Merging.

Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryotaro Shimizu, Hiroki Naganuma

CoRR, August, 2025

Transferring Visual Explainability of Self-Explaining Models through Task Arithmetic.

Yuya Yoshikawa, Ryotaro Shimizu, Takahiro Kawashima, Yuki Saito

CoRR, July, 2025

Static Word Embeddings for Sentence Semantic Representation.

Takashi Wada, Yuki Hirakawa, Ryotaro Shimizu, Takahiro Kawashima, Yuki Saito

CoRR, June, 2025

On Fairness of Task Arithmetic: The Role of Task Vectors.

Hiroki Naganuma, Kotaro Yoshida, Laura Gomezjurado Gonzalez, Takafumi Horie, Yuji Naraki, Ryotaro Shimizu

CoRR, May, 2025

Masked Language Prompting for Generative Data Augmentation in Few-shot Fashion Style Recognition.

Yuki Hirakawa, Ryotaro Shimizu

CoRR, April, 2025

Attributed Synthetic Data Generation for Zero-shot Domain-specific Image Classification.

Shijian Wang, Linxin Song, Ryotaro Shimizu, Masayuki Goto, Hanqian Wu

CoRR, April, 2025

Discovering Knowledge Deficiencies of Language Models on Massive Knowledge Base.

Linxin Song, Xuwei Ding, Jieyu Zhang, Taiwei Shi, Ryotaro Shimizu, Rahul Gupta, Yang Liu, Jian Kang, Jieyu Zhao

CoRR, March, 2025

Vision and Language Reference Prompt into SAM for Few-shot Segmentation.

Kosuke Sakurai, Ryotaro Shimizu, Masayuki Goto

CoRR, February, 2025

Sparse attention is all you need for pre-training on tabular data.

Tokimasa Isomura, Ryotaro Shimizu, Masayuki Goto

Neural Comput. Appl., January, 2025

Generating realistic synthetic tabular data with integrated LLM and diffusion models.

Tokimasa Isomura, Ryotaro Shimizu, Masayuki Goto

Neurocomputing, 2025

LLMOverTab: Tabular data augmentation with language model-driven oversampling.

Tokimasa Isomura, Ryotaro Shimizu, Masayuki Goto

Expert Syst. Appl., 2025

Disentangling Likes and Dislikes in Personalized Generative Explainable Recommendation.

Ryotaro Shimizu, Takashi Wada, Yu Wang, Johannes Kruse, Sean O'Brien, Sai Htaung Kham, Linxin Song, Yuya Yoshikawa, Yuki Saito, Fugee Tsung, Masayuki Goto, Julian J. McAuley

Proceedings of the ACM on Web Conference 2025, 2025

Fashionability-Enhancing Outfit Image Editing with Conditional Diffusion Models.

Qice Qin, Yuki Hirakawa, Ryotaro Shimizu, Takuya Furusawa, Edgar Simo-Serra

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

Mastering Task Arithmetic: τJp as a Key Indicator for Weight Disentanglement.

Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryosuke Yamaki, Ryotaro Shimizu, Yuki Saito, Julian J. McAuley, Hiroki Naganuma

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Template Matters: Understanding the Role of Instruction Templates in Multimodal Language Model Evaluation and Training.

Shijian Wang, Linxin Song, Jieyu Zhang, Ryotaro Shimizu, Ao Luo, Li Yao, Cunjian Chen, Julian J. McAuley, Hanqian Wu

CoRR, 2024

LARE: Latent Augmentation using Regional Embedding with Vision-Language Model.

Kosuke Sakurai, Tatsuya Ishii, Ryotaro Shimizu, Linxin Song, Masayuki Goto

CoRR, 2024

A Fashion Item Recommendation Model in Hyperbolic Space.

Ryotaro Shimizu, Yu Wang, Masanari Kimura, Yuki Hirakawa, Takashi Wada, Yuki Saito, Julian J. McAuley

CoRR, 2024

Explaining Black-box Model Predictions via Two-level Nested Feature Attributions with Consistency Property.

Yuya Yoshikawa, Masanari Kimura, Ryotaro Shimizu, Yuki Saito

CoRR, 2024

On permutation-invariant neural networks.

Masanari Kimura, Ryotaro Shimizu, Yuki Hirakawa, Ryosuke Goto, Yuki Saito

CoRR, 2024

An Empirical Analysis of GPT-4V's Performance on Fashion Aesthetic Evaluation.

Yuki Hirakawa, Takashi Wada, Kazuya Morishita, Ryotaro Shimizu, Takuya Furusawa, Sai Htaung Kham, Yuki Saito

Proceedings of the SIGGRAPH Asia 2024 Technical Communications, 2024

2023

Partial visual-semantic embedding: Fine-grained outfit image representation with massive volumes of tags via angular-based contrastive learning.

Ryotaro Shimizu, Takuma Nakamura, Masayuki Goto

Knowl. Based Syst., October, 2023

Fashion intelligence system: An outfit interpretation utilizing images and rich abstract tags.

Ryotaro Shimizu, Yuki Saito, Megumi Matsutani, Masayuki Goto

Expert Syst. Appl., 2023

Fashion-Specific Ambiguous Expression Interpretation with Partial Visual-Semantic Embedding.

Ryotaro Shimizu, Takuma Nakamura, Masayuki Goto

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

An explainable recommendation framework based on an improved knowledge graph attention network with massive volumes of side information.

Ryotaro Shimizu, Megumi Matsutani, Masayuki Goto

Knowl. Based Syst., 2022

Partial Visual-Semantic Embedding: Fashion Intelligence System with Sensitive Part-by-Part Learning.

Ryotaro Shimizu, Takuma Nakamura, Masayuki Goto

CoRR, 2022

Fashion-Specific Attributes Interpretation via Dual Gaussian Visual-Semantic Embedding.

Ryotaro Shimizu, Masanari Kimura, Masayuki Goto

CoRR, 2022