Yutaro Yamada

According to our database, Yutaro Yamada authored at least 17 papers between 2015 and 2024.

Collaborative distances:

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

2024

L3GO: Language Agents with Chain-of-3D-Thoughts for Generating Unconventional Objects.

Yutaro Yamada, Khyathi Chandu, Bill Yuchen Lin, Jack Hessel, Ilker Yildirim, Yejin Choi

CoRR, 2024

2023

Support recovery with Projected Stochastic Gates: Theory and application for linear models.

Soham Jana, Henry Li, Yutaro Yamada, Ofir Lindenbaum

Signal Process., December, 2023

Evaluating Spatial Understanding of Large Language Models.

Yutaro Yamada, Yihan Bao, Andrew K. Lampinen, Jungo Kasai, Ilker Yildirim

CoRR, 2023

Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations.

Jungo Kasai, Yuhei Kasai, Keisuke Sakaguchi, Yutaro Yamada, Dragomir Radev

CoRR, 2023

Surrogate-Assisted (1+1)-CMA-ES with Switching Mechanism of Utility Functions.

Yutaro Yamada, Kento Uchida, Shota Saito, Shinichi Shirakawa

Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023

When are Lemons Purple? The Concept Association Bias of Vision-Language Models.

Yingtian Tang, Yutaro Yamada, Yoyo Zhang, Ilker Yildirim

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

When are Lemons Purple? The Concept Association Bias of CLIP.

Yutaro Yamada, Yingtian Tang, Ilker Yildirim

CoRR, 2022

Can Wikipedia Help Offline Reinforcement Learning?

Machel Reid, Yutaro Yamada, Shixiang Shane Gu

CoRR, 2022

Does Robustness on ImageNet Transfer to Downstream Tasks?

Yutaro Yamada, Mayu Otani

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Support Recovery with Stochastic Gates: Theory and Application for Linear Models.

Soham Jana, Henry Li, Yutaro Yamada, Ofir Lindenbaum

CoRR, 2021

2020

Feature Selection using Stochastic Gates.

Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger

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

2018

Understanding adversarial training: Increasing local stability of supervised models through robust optimization.

Uri Shaham, Yutaro Yamada, Sahand Negahban

Neurocomputing, 2018

Deep supervised feature selection using Stochastic Gates.

Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger

CoRR, 2018

Defending against Adversarial Images using Basis Functions Transformations.

Uri Shaham, James Garritano, Yutaro Yamada, Ethan Weinberger, Alex Cloninger, Xiuyuan Cheng, Kelly P. Stanton, Yuval Kluger

CoRR, 2018

2017

Deep learning-based water-intake estimation method using second half of swallowing sound.

Yutaro Yamada, Masafumi Nishimura, Hiroshi Mineno, Takato Saito, Satoshi Kawasaki, Daizo Ikeda, Masaji Katagiri

Proceedings of the IEEE 6th Global Conference on Consumer Electronics, 2017

A Deep-Learning-Based Method of Estimating Water Intake.

Yutaro Yamada, Takato Saito, Satoshi Kawasaki, Daizo Ikeda, Masaji Katagiri, Masafumi Nishimura, Hiroshi Mineno

Proceedings of the 41st IEEE Annual Computer Software and Applications Conference, 2017

2015

Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization.

Uri Shaham, Yutaro Yamada, Sahand Negahban

CoRR, 2015