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| "description": "A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in\n advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains\n only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also\n including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.\n", | |
| "citation": "@article{allenai:arc,\n author = {Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and\n Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},\n title = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},\n journal = {arXiv:1803.05457v1},\n year = {2018},\n}\n", | |
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| "description": "A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in\n advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains\n only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also\n including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.\n", | |
| "citation": "@article{allenai:arc,\n author = {Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and\n Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},\n title = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},\n journal = {arXiv:1803.05457v1},\n year = {2018},\n}\n", | |
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