I am a research scientist at Sakana AI. Previously I was a PhD student in Statistics and Data Science at Yale, and worked at Meta, Allen Institute for AI, and CyberAgent AI Lab as a research intern. My current interests include agents, LLMs, and vision & language.
Research
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
NAACL 2025, System Demonstration track [Demo Video]-
Three-Dimensional Reconstruction Pre-Training as a Prior to Improve Robustness to Adversarial Attacks and Spurious Correlation
Yutaro Yamada, Fred Weiying Zhang, Yuval Kluger, Ilker Yildirim
Entropy 2024 Evaluating Spatial Understanding of Large Language Models
Yutaro Yamada, Yihan Bao, Andrew K. Lampinen, Jungo Kasai, Ilker Yildirim
TMLR 2024Evaluating gpt-4 and chatgpt on japanese medical licensing examinations
Jungo Kasai, Yuhei Kasai, Keisuke Sakaguchi, Yutaro Yamada, Dragomir Radev
Preprint, 2023-
When are Lemons Purple? The Concept Association Bias of Vision-Language Models
Yutaro Yamada*, Yingtian Tang*, Yoyo Zhang, Ilker Yildirim
EMNLP 2023 [Slides] Support Recovery with Stochastic Gates: Theory and Application for Linear Models
Soham Jana, Henry Li, Yutaro Yamada, Ofir Lindenbaum
Signal Processing 2023Can Wikipedia Help Offline Reinforcement Learning?
Machel Reid, Yutaro Yamada, Shixiang Shane Gu
Preprint, 2022Does Robustness on ImageNet Transfer to Downstream Tasks?
Yutaro Yamada, Mayu Otani
CVPR 2022Exploiting 3D Shape Bias towards Robust Vision
Yutaro Yamada, Sahand Negahban, Yuval Kluger, Ilker Yildirim
NeurIPS 2021 Workshop SVRHMFeature Selection using Stochastic Gates
Yutaro Yamada*, Ofir Lindenbaum*, Sahand Negahban, Yuval Kluger
ICML 2020Understanding Adversarial Training: Increasing local stability of supervised models through robust optimization
Uri Shaham, Yutaro Yamada, Sahand Negahban
Neurocomputing 2018