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--- |
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title: README |
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emoji: 🦀 |
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colorFrom: gray |
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colorTo: blue |
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sdk: static |
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pinned: false |
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--- |
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# MWP-T5: Fine-tuning with Numeracy for Math Word Problem Generation |
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This repository contains the code for the |
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paper [Fine-tuning with Numeracy for Math Word Problem Generation]() [[PDF]()] published at IEEE T4E 2023. |
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<img src="MWP-T5.jpg"> |
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You can access our source code [here](https://github.com/yashichawla/mwp-t5). If you would like to cite our work, please use |
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the following BiBTex entry: |
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``` |
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``` |
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# Performance |
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MWP-T5 achieves state-of-the-art performance on the MAWPS and PEN datasets. The following tables show the performance |
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of MWP-T5 and other models on the MAWPS and PEN datasets. For more information, please refer to the paper. |
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## MAWPS |
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| Model Name | BLEU-4 | ROUGE-L | METEOR | |
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|---------------------|:---------:|:---------:|:---------:| |
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| seq2seq-rnn | 0.153 | 0.362 | 0.175 | |
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| seq2seq-rnn + GLoVe | 0.592 | 0.705 | 0.412 | |
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| seq2seq-tf | 0.554 | 0.663 | 0.387 | |
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| GPT | 0.368 | 0.538 | 0.294 | |
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| GPT-pre | 0.504 | 0.664 | 0.391 | |
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| GPT2-mwp2eq | 0.596 | 0.715 | 0.427 | |
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| **MWP-T5** | **0.885** | **0.930** | **0.930** | |
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## PEN |
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| Model Name | BLEU-4 | ROUGE-L | METEOR | |
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|------------|:---------:|:---------:|:---------:| |
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| **MWP-T5** | **0.669** | **0.768** | **0.772** | |
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# Contact |
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Please feel free to contact us by emailing us to report any issues or suggestions, or if you have any further |
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questions. |
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Contact: - [Yashi Chawla](mailto:yashi.chawla1@gmail.com) |
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You can also contact the other maintainers listed below. |
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- [Chakita Muttaraju](mailto:chakitapesu@gmail.com) |
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- [Prajwal Anagani](mailto:prajwalanagani@gmail.com) |
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- [Parimala S](mailto:parimalas2001@gmail.com) |
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- [Gowri Srinivasa](mailto:gsrinivasa@pes.edu) |
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