I am a fourth-year PhD candidate at the University of Michigan in Ann Arbor advised by Lu Wang and Honglak Lee. I’m currently an intern at LG AI Research working on web agents. I am interested in test-time techniques for LLM reasoning, controlled generation, and knowledge attribution. I was fortunate to work in different places with so many amazing people. In summer 2023, I was AI2 working with Iz Beltagy and Hao Peng on training models to cite their pretraining data. In 2021, I was Amazon AWS working with Kathy Mckeown. Prior to that, I was an intern at Naver Labs Europe where I worked on Controllable Text Generation and Energy-based models with Hady Elsahar and Marc Dymetman.
On a side note, I’m an avid reader of philosophy of mind, and an all-time listener of uplifting trance music. In my free time, I play the piano, write, and produce my own music. If you’d like to chat about research, mentoring, or potentially collaborate, ping me at [lastname]m@umich.edu.
News
July 2025 Gave an invited talk on ThinkPRM at Tsinghua University. Here are the slides
April 2025 Our work on Generative Process Reward Models is out!.
April 2025 Was awarded the CSE Service Award at UMich! 🎉
April 2025 Gave a talk on model merging at DLCT. Here are the Slides
March 2025 Co-organized the NLP@Michigan Day
December 2024 My work at Cohere on large-scale model merging optimization is out!
July 2024: Two papers accepted at COLM and ACL Findings!
June 2024: Started my internship at Cohere!
April 2024: My work with Ai2 on on source-aware training is released on arxiv
March, 2024: Gave a talk on LLM Reasoning at ML Collective DLCT reading group. Video is here.
Nov, 2023: Gave an invited talk at NAVER Labs Europe on Discriminator-Guided Chain-of-Thought. Slides are here.
Oct, 2023: Two papers accepted at EMNLP 2023 (Findings and main)!
May, 2023: Three papers accepted at ACL 2023 (two at the main conference and one at Findings)!
Nov 30th, 2022: I was awarded the Rackham Fellowship for Outstanding International Students!
Highlighted Papers
(Likely outdated; For an up-to-date list, visit my google scholar)
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang. Exploring Demonstration Ensembling for In-context Learning. ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation Models. [Paper].
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang. Few-shot Reranking for Multi-hop QA via Language Model Prompting. ACL 2023 [Paper] [Code].
Muhammad Khalifa, Miguel Ballesteros, and Kathleen McKeown. 2021. A Bag of Tricks for Dialogue Summarization. EMNLP 2021 (short paper) [Paper].
Muhammad Khalifa, Muhammad Abdul-Mageed, Khaled Shaalan. “Self-Training Pre-Trained Language Models for Zero-and Few-Shot Multi-Dialectal Arabic Sequence Labeling.” EACL 2021. [Paper] [Code] [Bibtex]
Muhammad Khalifa*, Hady Elsahar*, Marc Dymetman*. “A Distributional Approach to Controlled Text Generation”. ICLR 2021. [Paper] [Code] [Blog]