Papers by Brian Jin
How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact (2021.findings-acl)
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| Challenge: | Recent years have seen many breakthroughs in natural language processing (NLP), transitioning it from a mostly theoretical field to one with many real-world applications. |
| Approach: | They propose a moral philosophy definition of social good and a framework to evaluate the direct and indirect real-world impact of NLP tasks. |
| Outcome: | The proposed framework evaluates the direct and indirect real-world impact of NLP tasks and adopts the methodology of global priorities research to identify priority causes for NLP research. |
Using a Human-AI Teaming Approach to Create and Curate Scientific Datasets with the SciLire System (2026.eacl-demo)
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Necva Bölücü, Jessica Irons, Changhyun Lee, Brian Jin, Maciej Rybinski, Huichen Yang, Andreas Duenser, Stephen Wan
| Challenge: | rapid growth of scientific literature has made manual extraction of structured knowledge increasingly impractical. |
| Approach: | They propose a system for creating datasets from scientific literature that integrates human-AI teaming principles and iterative workflows. |
| Outcome: | The proposed system improves extraction fidelity and facilitates efficient dataset creation. |