Tricks for Training Sparse Translation Models | 0 | 0.34 | 2022 |
Generative Context Pair Selection for Multi-hop Question Answering. | 0 | 0.34 | 2021 |
Learning with Instance Bundles for Reading Comprehension. | 0 | 0.34 | 2021 |
Easy, Reproducible and Quality-Controlled Data Collection with Crowdaq | 0 | 0.34 | 2020 |
Benefits of Intermediate Annotations in Reading Comprehension | 1 | 0.35 | 2020 |
Evaluating Models' Local Decision Boundaries via Contrast Sets. | 0 | 0.34 | 2020 |
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. | 4 | 0.39 | 2019 |
Comprehensive Multi-Dataset Evaluation of Reading Comprehension. | 0 | 0.34 | 2019 |
PoMo: Generating Entity-Specific Post-Modifiers in Context. | 0 | 0.34 | 2019 |
Generating Natural Adversarial Examples. | 0 | 0.34 | 2018 |
Generating Natural Adversarial Examples. | 33 | 0.84 | 2017 |
CMUQA: Multiple-Choice Question Answering at NTCIR-12 QA Lab-2 Task. | 0 | 0.34 | 2016 |
CMU-LTI at KBP 2015 Event Track. | 0 | 0.34 | 2015 |