Portrait of Kevin Farhat

Kevin Farhat

Researching flexible language models.

I’m at Ai2 on the OLMo team. I’m especially interested in systems that can adapt over time while still working under real deployment constraints.

What I’m working on

I helped develop FlexOLMo, and now apply related ideas in federated learning setups to train on privacy-sensitive cancer data across institutions through the Cancer AI Alliance.

Previously, I worked at TrueMedia with Oren Etzioni on deepfake detection systems intended to help safeguard the 2024 U.S. election.

I earned my BS/MS in Computer Science at the University of Washington, where I worked with Akari Asai in the H2Lab under Hannaneh Hajishirzi.

Current interests: adaptive LLMs, continual learning, flexible and modular models, and agents.

Selected Papers

NeurIPS 2025 Spotlight

FlexOLMo: Open Language Models for Flexible Data Use

Weijia Shi, Akshita Bhagia, Kevin Farhat, Niklas Muennighoff, Pete Walsh, Jacob Morrison, Dustin Schwenk, Shayne Longpre, Jake Poznanski, Allyson Ettinger, Daogao Liu, Margaret Li, Dirk Groeneveld, Mike Lewis, Wen-tau Yih, Luca Soldaini, Kyle Lo, Noah A. Smith, Luke Zettlemoyer, Pang Wei Koh, Hannaneh Hajishirzi, Ali Farhadi, Sewon Min

Read paper
DMLR @ ICML 2024

The Tug-of-War Between Deepfake Generation and Detection

Hannah Lee, Changyeon Lee, Kevin Farhat, Lin Qiu, Steve Geluso, Aerin Kim, Oren Etzioni

Read paper
APAI @ CVPR 2026

Deepfake-Eval-2024: A Multi-Modal In-the-Wild Benchmark of Deepfakes Circulated in 2024

Nuria Alina Chandra, Ryan Murtfeldt, Lin Qiu, Arnab Karmakar, Hannah Lee, Emmanuel Tanumihardja, Kevin Farhat, Ben Caffee, Sejin Paik, Changyeon Lee, Jongwook Choi, Aerin Kim, Oren Etzioni

Read paper

Outside Work

Outside of work, I like playing and watching soccer, traveling, and carrot cake .