Search Results for author: Katherine Lee

Found 4 papers, 4 papers with code

Deduplicating Training Data Makes Language Models Better

1 code implementation14 Jul 2021 Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini

As a result, over 1% of the unprompted output of language models trained on these datasets is copied verbatim from the training data.

Language Modelling

Extracting Training Data from Large Language Models

1 code implementation14 Dec 2020 Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, Alina Oprea, Colin Raffel

We demonstrate our attack on GPT-2, a language model trained on scrapes of the public Internet, and are able to extract hundreds of verbatim text sequences from the model's training data.

Language Modelling

WT5?! Training Text-to-Text Models to Explain their Predictions

2 code implementations30 Apr 2020 Sharan Narang, Colin Raffel, Katherine Lee, Adam Roberts, Noah Fiedel, Karishma Malkan

Neural networks have recently achieved human-level performance on various challenging natural language processing (NLP) tasks, but it is notoriously difficult to understand why a neural network produced a particular prediction.

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

17 code implementations arXiv 2019 Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu

Transfer learning, where a model is first pre-trained on a data-rich task before being fine-tuned on a downstream task, has emerged as a powerful technique in natural language processing (NLP).

Common Sense Reasoning Question Answering +3

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