Adam Lelkes
I am a Senior Research Scientist at Google DeepMind, working on generative AI research.
Before joining Google, I received my Ph.D. in Mathematics at the University of Illinois at Chicago where I was advised by Lev Reyzin and György Turán, and was working on problems in computational complexity theory, combinatorial optimization, and machine learning.
Research Areas
Authored Publications
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Google
SEMQA: Semi-Extractive Multi-Source Question Answering
Haitian Sun
NAACL (2024) (to appear)
Understanding Generative Retrieval at Scale
Ronak Pradeep
Jimmy Lin
EMNLP 2023
Automated LOINC Standardization Using Pre-trained Large Language Models
Eric Loreaux
Emma Chesley
Paul Gamble
Martin Seneviratne
Ming-Jun Chen
PMLR (2022), pp. 343-355
Instability in clinical risk prediction models using deep learning
Daniel Lopez-Martinez
Alex Yakubovich
Martin Seneviratne
Akshit Tyagi
Ethan Steinberg
N. Lance Downing
Ron C. Li
Keith E. Morse
Nigam H. Shah
Ming-Jun Chen
Proceedings of the 2nd Machine Learning for Health symposium, PMLR (2022), pp. 552-565
Investigating Rumor News Using Agreement-Aware Search
Jingbo Shang
Jiaming Shen
Tianhang Sun
Xingbang Liu
Anja Gruenheid
Cong Yu
Jiawei Han
CIKM (2018)
