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cs.LG2024
DataComp-LM: In search of the next generation of training sets for language models
Jeffrey Li, Alex Fang, Georgios Smyrnis +56
We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardize…
cs.LG2024
Accelerated Parameter-Free Stochastic Optimization
Itai Kreisler, Maor Ivgi, Oliver Hinder +1
We propose a method that achieves near-optimal rates for smooth stochastic convex optimization and requires essentially no prior knowledge of problem parameters. This improves on p…
cs.LG2021
Achieving Model Robustness through Discrete Adversarial Training
Maor Ivgi, Jonathan Berant
Discrete adversarial attacks are symbolic perturbations to a language input that preserve the output label but lead to a prediction error. While such attacks have been extensively…