Arman


Assistant Professor
CS Department
Yale University

Arman Cohan

I am an Assistant Professor in the Computer Science Department at Yale University.
Prior to joining Yale, I was a Research Scientist at Allen Institute for AI (AI2).

At Yale, I lead the Natural Language Processing lab. My research spans various problems at the intersection of NLP and Machine Learning, including large language models, representation learning, retrieval and knowledge-intensive systems, and applications in specialized domains.
Currently, I am particularly interested in in-depth understanding of LLMs and their capabilities, from both evaluation and interpretability perspectives. Additionally, I'm interested in developing reasoning systems in knowledge-intensive and specialized environments. Finally, my lab also works on building LLM-based systems that can help scientists and other domain experts.

→ For current areas of focus, my research group, Ph.D. student openings, and other available opportunities, please visit our lab website.


Teaching
  • [Spring 2026] - CPSC 4770/5770: Large Language Models -- From Foundations to Modern Practice
    This course will cover the fundamentals of large language models (LLMs) from the ground up, aiming to provide a comprehensive understanding of the field and its modern practice. This course is designed for upper undergraduates and graduate students, requiring prior knowledge in introductory machine learning or artificial intelligence and aims to give students a strong foundation in the fields. Successfully completing the course will enable students to build their own LLM-based systems, and apply them to real-world problems.
  • [Spring 2025] - CPSC 477/577: Natural Language Processing -- Language Modeling
    This edition of the course primarily focuses on the fundamentals of natural language processing (NLP) with a strong emphasis on language modeling. This course is designed for upper undergraduates and graduate students, requiring prior knowledge in introductory machine learning or artificial intelligence.
  • [Spring 2024] - CPSC 477/577: Natural Language Processing
    This course aims to give students a strong foundation in the field of NLP, including early machine learning methods for NLP and modern neural network-based methods and large language models.
  • [Fall 2023] - CPSC 488/588: AI Foundation Models
    This course focuses on building blocks of foundation models. While the course primarily focuses on advances on LLMs, we will also cover foundation models in computer vision, as well as multi-modal foundation models.
  • [Spring 2023] - CPSC 670: Topics in Natural Language Processing
    This seminar course is focused on Large Language Models and other recent advances in NLP.



Publications
  • For most recent list of publications please refer to my Google Scholar page.


Contact