Ryo Kamoi

Ryo Kamoi

鴨井 遼 (ja)

Ph.D. Student

Penn State University

He is a CS Ph.D. student at Penn State University advised by Dr. Rui Zhang. He is broadly interested in Natural Language Processing, with a specific focus on building trustworthy NLP systems. He received his master’s degree in CS from UT Austin where he was advised by Dr. Greg Durrett, and received his bachelor’s degree in Statistics from Keio University where he was advised by Dr. Kei Kobayashi.

  • Trustworthy NLP Systems
  • Detecting and Mitigating Errors in Responses from LLMs
  • Evaluation of LLMs
  • Fact Checking
  • Text Summarization
  • Ph.D. in Computer Science, 2023 -

    Penn State University

  • M.S. in Computer Science, 2020 - 2022

    University of Texas at Austin

  • B.E. in Statistics, 2016 - 2020

    Keio University


When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs PDF Cite
(2024). TACL (to appear).
AAAR-1.0: Assessing AI's Potential to Assist Research PDF Cite
(2024). arXiv preprint arXiv:2410.22394.
Evaluating LLMs at Detecting Errors in LLM Responses PDF Cite Code Dataset Poster
(2024). COLM 2024.
Direct-Inverse Prompting: Analyzing LLMs' Discriminative Capacity in Self-Improving Generation PDF Cite
(2024). arXiv preprint arXiv:2407.11017.
DocMath-Eval: Evaluating Numerical Reasoning Capabilities of LLMs in Understanding Long Documents with Tabular Data PDF Cite
(2024). ACL 2024.
Fair Abstractive Summarization of Diverse Perspectives PDF Cite
(2024). NAACL 2024.
WiCE: Real-World Entailment for Claims in Wikipedia PDF Cite Dataset Slides
(2023). EMNLP 2023.
Efficient Unknown Object Detection with Discrepancy Networks for Semantic Segmentation PDF Cite
(2021). NeurIPS Workshop on Machine Learning for Autonomous Driving.
Alternative methods for fast and stable GAN Cite
(2020). MIRU.
Out-of-Distribution Detection with Likelihoods Assigned by Deep Generative Models Using Multimodal Prior Distributions PDF Cite
(2020). The AAAI’s Workshop on Artificial Intelligence Safety.
Why is the Mahalanobis Distance Effective for Anomaly Detection? PDF Cite
(2020). arXiv preprint arXiv:2003.00402.

Work Experience

Amazon - Applied Scientist Internship Jul 2021 – Dec 2021 Cambridge, U.K.
Research on the quality evaluation of Alexa

Services

NLP Colloquium (NLPコロキウム) - Staff Mar 2024 – Present

Awards

Scholarship for alumni of Keio University to pursue degrees at overseas graduate schools
Graduation with highest honors - First place in the Department of Mathematics at Keio University