You can also find my articles on my Semantic Scholar profile.

DoG is SGD’s Best Friend: A Parameter-Free Dynamic Step Size Schedule

Maor Ivgi, Oliver Hinder, Yair Carmon. Published in Preprint

DoG is a tuning-free dynamic SGD step size formula, backed by strong theoretical guarantees and empirically demonstrated over many domains and model-architectures to achieve comparable results to well-tuned SGD with best-practice learning-rate schedule.

Efficient Long-Text Understanding with Short-Text Models

Maor Ivgi, Uri Shaham, Jonathan Berant. Published in TACL 2023, will be presented in ACL 2023

Can short-range LMs perform long-range reasoning? They can!
In this work, we propose the SLiding-Encoder and Decoder (SLED) which leverages existing battle-proven enc-dec LMs to operate over long-range NLU tasks.

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

SCROLLS is a suite of datasets that require synthesizing information over long texts. The benchmark includes seven natural language tasks across multiple domains, including summarization, question answering, and natural language inference.