| Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets | 0 | 0.34 | 2022 |
| When to Use Multi-Task Learning vs Intermediate Fine-Tuning for Pre-Trained Encoder Transfer Learning | 0 | 0.34 | 2022 |
| Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks | 0 | 0.34 | 2022 |
| ReCLIP: A Strong Zero-Shot Baseline for Referring Expression Comprehension | 1 | 0.40 | 2022 |
| Paired Examples as Indirect Supervision in Latent Decision Models. | 0 | 0.34 | 2021 |
| Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization. | 0 | 0.34 | 2021 |
| A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers | 0 | 0.34 | 2021 |
| Competency Problems - On Finding and Removing Artifacts in Language Data. | 0 | 0.34 | 2021 |
| Generative Context Pair Selection for Multi-hop Question Answering. | 0 | 0.34 | 2021 |
| Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering | 0 | 0.34 | 2021 |
| COVR - A Test-Bed for Visually Grounded Compositional Generalization with Real Images. | 0 | 0.34 | 2021 |
| Learning with Instance Bundles for Reading Comprehension. | 0 | 0.34 | 2021 |
| Improving Compositional Generalization in Semantic Parsing | 0 | 0.34 | 2020 |
| IIRC: A Dataset of Incomplete Information Reading Comprehension Questions. | 0 | 0.34 | 2020 |
| Easy, Reproducible and Quality-Controlled Data Collection with Crowdaq | 0 | 0.34 | 2020 |
| Multi-Step Inference for Reasoning Over Paragraphs. | 0 | 0.34 | 2020 |
| MedICaT: A Dataset of Medical Images, Captions, and Textual References | 0 | 0.34 | 2020 |
| TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions. | 0 | 0.34 | 2020 |
| Break It Down: A Question Understanding Benchmark. | 0 | 0.34 | 2020 |
| Interpreting Predictions of NLP Models. | 0 | 0.34 | 2020 |
| Benefits of Intermediate Annotations in Reading Comprehension | 1 | 0.35 | 2020 |
| MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics. | 0 | 0.34 | 2020 |
| Learning from Task Descriptions. | 0 | 0.34 | 2020 |
| Evaluating Models' Local Decision Boundaries via Contrast Sets. | 0 | 0.34 | 2020 |
| Obtaining Faithful Interpretations from Compositional Neural Networks | 0 | 0.34 | 2020 |
| Neural Module Networks for Reasoning over Text | 1 | 0.35 | 2020 |
| Evaluating Question Answering Evaluation | 0 | 0.34 | 2019 |
| Analyzing Compositionality in Visual Question Answering. | 0 | 0.34 | 2019 |
| 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 |
| QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions | 1 | 0.35 | 2019 |
| Global Reasoning over Database Structures for Text-to-SQL Parsing | 2 | 0.36 | 2019 |
| Do NLP Models Know Numbers? Probing Numeracy in Embeddings | 2 | 0.38 | 2019 |
| Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing | 3 | 0.38 | 2019 |
| Linguistic Knowledge and Transferability of Contextual Representations. | 4 | 0.38 | 2019 |
| Iterative Search for Weakly Supervised Semantic Parsing | 2 | 0.36 | 2019 |
| AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models | 0 | 0.34 | 2019 |
| Reasoning Over Paragraph Effects in Situations. | 0 | 0.34 | 2019 |
| Grammar-based Neural Text-to-SQL Generation. | 0 | 0.34 | 2019 |
| Universal Adversarial Triggers for Attacking and Analyzing NLP | 10 | 0.58 | 2019 |
| Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning | 0 | 0.34 | 2019 |
| On Making Reading Comprehension More Comprehensive | 0 | 0.34 | 2019 |
| Deep contextualized word representations. | 420 | 10.99 | 2018 |
| Structured Alignment Networks for Matching Sentences. | 0 | 0.34 | 2018 |
| QuAREL: A Dataset and Models for Answering Questions about Qualitative Relationships | 1 | 0.35 | 2018 |
| AllenNLP: A Deep Semantic Natural Language Processing Platform. | 34 | 0.93 | 2018 |
| Never-ending learning. | 18 | 0.95 | 2018 |
| Neural Semantic Parsing. | 0 | 0.34 | 2018 |
| Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge. | 0 | 0.34 | 2017 |
| Neural Semantic Parsing with Type Constraints for Semi-Structured Tables. | 22 | 0.76 | 2017 |
