1 code implementation • EMNLP 2021 • Zheng Yuan, Shiva Taslimipoor, Christopher Davis, Christopher Bryant
In this paper, we show how a multi-class grammatical error detection (GED) system can be used to improve grammatical error correction (GEC) for English.
no code implementations • 15 Jan 2024 • Christopher Davis, Andrew Caines, Øistein Andersen, Shiva Taslimipoor, Helen Yannakoudakis, Zheng Yuan, Christopher Bryant, Marek Rei, Paula Buttery
Thanks to recent advances in generative AI, we are able to prompt large language models (LLMs) to produce texts which are fluent and grammatical.
no code implementations • 15 Nov 2023 • Richard Diehl Martinez, Zebulon Goriely, Hope McGovern, Christopher Davis, Andrew Caines, Paula Buttery, Lisa Beinborn
We describe our team's contribution to the STRICT-SMALL track of the BabyLM Challenge.
no code implementations • 17 Jul 2023 • Andrew Caines, Luca Benedetto, Shiva Taslimipoor, Christopher Davis, Yuan Gao, Oeistein Andersen, Zheng Yuan, Mark Elliott, Russell Moore, Christopher Bryant, Marek Rei, Helen Yannakoudakis, Andrew Mullooly, Diane Nicholls, Paula Buttery
The recent release of very large language models such as PaLM and GPT-4 has made an unprecedented impact in the popular media and public consciousness, giving rise to a mixture of excitement and fear as to their capabilities and potential uses, and shining a light on natural language processing research which had not previously received so much attention.
1 code implementation • 28 Oct 2022 • Christopher Davis, Christopher Bryant, Andrew Caines, Marek Rei, Paula Buttery
Targeted studies testing knowledge of subject-verb agreement (SVA) indicate that pre-trained language models encode syntactic information.
no code implementations • SEMEVAL 2019 • Christopher Davis, Luana Bulat, Anita Lilla Vero, Ekaterina Shutova
Multimodal semantic models that extend linguistic representations with additional perceptual input have proved successful in a range of natural language processing (NLP) tasks.
2 code implementations • 8 Jan 2019 • Joseph DeRose, Risa H. Wechsler, Matthew R. Becker, Michael T. Busha, Eli S. Rykoff, Niall MacCrann, Brandon Erickson, August E. Evrard, Andrey Kravtsov, Daniel Gruen, Sahar Allam, Santiago Avila, Sarah Bridle, David Brooks, Elizabeth Buckley-Geer, Aurelio Carnero Rosell, Matias Carrasco Kind, Jorge Carretero, Francisco J. Castander, Ross Cawthon, Martin Crocce, Luiz N. da Costa, Christopher Davis, Juan De Vicente, Jörg P. Dietrich, Peter Doel, Alex Drlica-Wagner, Pablo Fosalba, Josh Frieman, Juan Garcia-Bellido, Gaston Gutierrez, Will G. Hartley, Devon L. Hollowood, Ben Hoyle, David J. James, Elisabeth Krause, Kyler Kuehn, Nikolay Kuropatkin, Marcos Lima, Marcio A. G. Maia, Felipe Menanteau, Christopher J. Miller, Ramon Miquel, Ricardo L. C. Ogando, Andrés Plazas Malagón, A. Kathy Romer, Eusebio Sanchez, Rafe Schindler, Santiago Serrano, Ignacio Sevilla-Noarbe, Mathew Smith, Eric Suchyta, Molly E. C. Swanson, Gregory Tarle, Vinu Vikram
We show that the weak-lensing shear catalog, redMaGiC galaxy catalogs and redMaPPer cluster catalogs provide plausible realizations of the same catalogs in the DES Y1 data by comparing their magnitude, color and redshift distributions, angular clustering, and mass-observable relations, making them useful for testing analyses that use these samples.
Cosmology and Nongalactic Astrophysics