Papers by Austin Huang
Understanding HTML with Large Language Models (2023.findings-emnlp)
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Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin Huang, Aakanksha Chowdhery, Sharan Narang, Noah Fiedel, Aleksandra Faust
| Challenge: | Large language models have shown exceptional performance on a variety of natural language tasks, but their capabilities for HTML understanding have not been fully explored. |
| Approach: | They propose to use HTML understanding models to parse HTML and perform HTML navigation tasks with a large-scale HTML dataset. |
| Outcome: | The proposed models perform 50% more tasks with 192x less data than the previous best supervised model. |