Papers by John Nguyen
A New Corpus to Support Text Mining for the Curation of Metabolites in the ChEBI Database (L18-1)
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Matthew Shardlow, Nhung Nguyen, Gareth Owen, Claire O’Donovan, Andrew Leach, John McNaught, Steve Turner, Sophia Ananiadou
| Challenge: | a corpus of 200 abstracts and 100 full text papers which have been annotated with named entities and relations in the biomedical domain is part of the OpenMinTeD project. |
| Approach: | They propose to annotate 200 abstracts and 100 full text papers with entities and relations in the biomedical domain as part of the OpenMinTeD project. |
| Outcome: | The proposed corpus can be used within ChEBI to facilitate text and data mining and integrate with the OpenMinTeD text and database platform. |
Byte Latent Transformer: Patches Scale Better Than Tokens (2025.acl-long)
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Artidoro Pagnoni, Ramakanth Pasunuru, Pedro Rodriguez, John Nguyen, Benjamin Muller, Margaret Li, Chunting Zhou, Lili Yu, Jason E Weston, Luke Zettlemoyer, Gargi Ghosh, Mike Lewis, Ari Holtzman, Srini Iyer
| Challenge: | Existing large language models (LLMs) are trained on bytes, except for tokenization, which groups bytes into a static set of tokens. |
| Approach: | They propose a new byte-level LLM architecture that encodes bytes into dynamically sized patches, which serve as the primary units of computation. |
| Outcome: | The proposed architecture matches tokenization-based models with improvements in inference efficiency and robustness. |