Papers with machine learning conferences
Neural Speed Reading Audited (2020.findings-emnlp)
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| Challenge: | Several approaches to neural speed reading have been presented at major NLP and machine learning conferences in 2017–20. |
| Approach: | They propose to model "human speed reading" for more efficient NLP, including document classification and named entity recognition. |
| Outcome: | The proposed approach has 7% error reduction and 136x speed-up over the state-of-the-art in neural speed reading. |
The Impact of Large Language Models in Academia: from Writing to Speaking (2025.findings-acl)
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| Challenge: | Large language models (LLMs) are impacting human society, especially in textual information. |
| Approach: | They propose to build an automated monitoring platform to track the impact of large language models on human expression. |
| Outcome: | The results show that LLM-style words such as significant are used more frequently in abstracts and oral presentations. |