Papers by Zhen Nie
Easy, Reproducible and Quality-Controlled Data Collection with CROWDAQ (2020.emnlp-demos)
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Qiang Ning, Hao Wu, Pradeep Dasigi, Dheeru Dua, Matt Gardner, Robert L. Logan IV, Ana Marasović, Zhen Nie
| Challenge: | Efficient data collection is important for advancing research and building time-sensitive applications. |
| Approach: | They propose an open-source platform that standardizes the data collection pipeline . it includes customizable user interface components, automated annotator qualification, and saved pipelines . |
| Outcome: | The proposed platform simplifies data annotation significantly on diverse datasets . it can be used by researchers and engineers to improve reproducibility and minimize overhead . |
Distillation Enhanced Generative Retrieval (2024.findings-acl)
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| Challenge: | Generative retrieval is a promising new paradigm in text retrieval that generates identifier strings of relevant passages as the retrieval target. |
| Approach: | They propose a framework that leverages generative language models to enhance generative retrieval by distillation. |
| Outcome: | The proposed framework achieves state-of-the-art performance among the generative retrieval methods. |