About me
I’m an AI researcher, entrepreneur, and lecturer with extensive experience in practical applications of large language models (LLMs). As a Ph.D. candidate at Tel-Aviv University, advised by Prof. Jonathan Berant’ and Dr. Yair Carmon’, I focus on improving LLMs for real-world use. I graduated summa cum laude from the Hebrew University of Jerusalem and am on track to graduate with my Ph.D. from Tel-Aviv University.
I co-founded Demystify-AI, where I served as CTO, developing an innovative explainable AI platform for healthcare and finance. Previously, I implemented advanced AI solutions for computer vision, network analysis, and more for the energy industry as well as for government law enforcement, gaining valuable experience in deploying highly dependable and scalable products.
Currently, I work with Meta’s GenAI team and consult for leading Israeli companies on developing cutting-edge NLP and data science products. Additionally, I developed and teach a popular NLP course at Tel-Aviv University, which has educated nearly 500 students over the past two years.
Publications
From Loops to Oops: Fallback Behaviors of Language Models Under Uncertainty
Maor Ivgi, Ori Yoran, Jonathan Berant, Mor Geva. Published in Arxiv preprint
DataComp-LM: In search of the next generation of training sets for language models
Jeffrey Li*, Alex Fang*, Georgios Smyrnis*, Maor Ivgi*, Matt Jordan, Samir Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Chandu, Thao Nguyen, Igor Vasiljevic, Sham Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave*, Ludwig Schmidt*, Vaishaal Shankar*. Published in Arxiv preprint
In-Context Learning with Long-Context Models: An In-Depth Exploration
Amanda Bertsch, Maor Ivgi, Uri Alon, Jonathan Berant, Matthew R. Gormley, Graham Neubig. Published in Arxiv preprint
Accelerated Parameter-Free Stochastic Optimization
Itai Kreisler, Maor Ivgi, Oliver Hinder, Yair Carmon. Published in COLT (2024)
ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding
Uri Shaham, Maor Ivgi, Avia Efrat, Jonathan Berant, Omer Levy. Published in Findings of EMNLP 2023
DoG is SGD’s Best Friend: A Parameter-Free Dynamic Step Size Schedule
Maor Ivgi, Oliver Hinder, Yair Carmon. Published in ICML (2023)
Efficient Long-Text Understanding with Short-Text Models
Maor Ivgi, Uri Shaham, Jonathan Berant. Published in TACL 2023, presented in ACL 2023
Scaling Laws Under the Microscope: Predicting Transformer Performance from Small Scale Experiments
Maor Ivgi, Yair Carmon, Jonathan Berant. Published in Findings of EMNLP 2022
SCROLLS: Standardized CompaRison Over Long Language Sequences
Uri Shaham, Elad Segal, Maor Ivgi, Avia Efrat, Ori Yoran, Adi Haviv, Ankit Gupta, Wenhan Xiong, Mor Geva, Jonathan Berant, Omer Levy. Published in EMNLP 2022
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics
Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna and James Zou. Published in MDPI (vol. 13), 2021
Achieving Model Robustness through Discrete Adversarial Training
Maor Ivgi and Jonathan Berant. Published in EMNLP 2021
Scene Graph to Image Generation with Contextualized Object Layout Refinement
Maor Ivgi, Yaniv Benny, Avichai Ben-David, Jonathan Berant, and Lior Wolf. Published in ICIP 2021
Teaching
Natural Langauge Processing, spring 2023
Undergraduate course, Tel-Aviv University, School of CS
Natural Langauge Processing, fall 2023
Undergraduate course, Tel-Aviv University, School of CS
Natural Langauge Processing, fall 2022
Undergraduate course, Tel-Aviv University, School of CS
Patents
A Machine Learning Model Blind-Spot Detection System and Method
Maor Ivgi and Yuval Dafna. Submission: U.S. Provisional Patent Application No. 63/170,517 f.