Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences (N18-1)
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| Challenge: | Using a dataset of 6,500+ questions, we found that human solvers achieved an F1-score of 88.1%. |
| Approach: | They propose a reading comprehension challenge in which questions can only be answered by taking into account information from multiple sentences. |
| Outcome: | The proposed reading comprehension challenge is based on a reading comprehension dataset with 6,500+ questions and 1000+ paragraphs across 7 domains. |
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| Challenge: | Getting machines to "understand" text is a vast and long-standing problem, made more challenging by the fact that it is not even clear what it means to understand text. |
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What Makes Reading Comprehension Questions Difficult? (2022.acl-long)
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| Challenge: | a recent study shows that natural language understanding benchmarks are not able to measure future progress . a crowdsourcing approach is needed to collect diverse examples without sacrificing diversity or coverage. |
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Challenging Reading Comprehension on Daily Conversation: Passage Completion on Multiparty Dialog (N18-1)
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| Challenge: | Existing approaches to reading comprehension on multiparty dialogs have focused on children's stories or newswire. |
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Evaluating the Rationale Understanding of Critical Reasoning in Logical Reading Comprehension (2023.emnlp-main)
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| Challenge: | Recent large language models (e.g., InstructGPT) struggle to answer subquestions written for the incorrect options of the main questions, implying that they have a limited capability for explaining why incorrect alternatives should be eliminated. |
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How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks (D18-1)
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| Challenge: | Recent research addresses reading comprehension, where examples consist of (question, passage, answer) tuples. |
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A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference (N18-1)
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| Challenge: | et al., 1996, show that many of the most actively studied problems in NLP depend in large part on natural language understanding (NLU). |
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| Challenge: | Recent deep-learning based models suffer from reasoning over long documents and do not trivially generalize to cases where the answer is not present as a span. |
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Comprehensive Multi-Dataset Evaluation of Reading Comprehension (D19-58)
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| Challenge: | Recent research aims to facilitate training and evaluation on several reading comprehension datasets at the same time. |
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| Challenge: | DuoRC contains 186,089 unique question-answer pairs created from 7680 movie plots . |
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