Nikita Pavlichenko
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## Model description
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This is a T5 Large fine-tuned for crowdsourced text aggregation tasks. The model takes multiple performers' responses and yields a single aggregated response. This approach was introduced for the first time during [VLDB 2021 Crowd Science Challenge](https://crowdscience.ai/challenges/vldb21) and originally implemented at the second-place competitor's [GitHub](https://github.com/A1exRey/VLDB2021_workshop_t5).
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## How to use
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### BibTeX entry and citation info
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```bibtex
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@misc{pavlichenko2021vox,
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## Model description
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This is a T5 Large fine-tuned for crowdsourced text aggregation tasks. The model takes multiple performers' responses and yields a single aggregated response. This approach was introduced for the first time during [VLDB 2021 Crowd Science Challenge](https://crowdscience.ai/challenges/vldb21) and originally implemented at the second-place competitor's [GitHub](https://github.com/A1exRey/VLDB2021_workshop_t5). The [paper](http://ceur-ws.org/Vol-2932/short2.pdf) describing this model was presented at the [2nd Crowd Science Workshop](https://crowdscience.ai/conference_events/vldb21).
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## How to use
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### BibTeX entry and citation info
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```bibtex
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@inproceedings{Pletenev:21,
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author = {Pletenev, Sergey},
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title = {{Noisy Text Sequences Aggregation as a Summarization Subtask}},
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year = {2021},
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booktitle = {Proceedings of the 2nd Crowd Science Workshop: Trust, Ethics, and Excellence in Crowdsourced Data Management at Scale},
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pages = {15--20},
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address = {Copenhagen, Denmark},
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issn = {1613-0073},
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url = {http://ceur-ws.org/Vol-2932/short2.pdf},
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language = {english},
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}
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```
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```bibtex
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@misc{pavlichenko2021vox,
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