Papers
See AI2's Award Winning Papers
Learn more about AI2's Lasting Impact Award
Viewing 121-130 of 214 papers
Reasoning Over Paragraph Effects in Situations
Kevin Lin, Oyvind Tafjord, Peter Clark, Matt GardnerEMNLP • MRQA Workshop • 2019 A key component of successfully reading a passage of text is the ability to apply knowledge gained from the passage to a new situation. In order to facilitate progress on this kind of reading, we present ROPES, a challenging benchmark for reading…Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text
Bhavana Dalvi Mishra, Niket Tandon, Antoine Bosselut, Wen-tau Yih, Peter ClarkEMNLP • 2019 Our goal is to better comprehend procedural text, e.g., a paragraph about photosynthesis, by not only predicting what happens, but why some actions need to happen before others. Our approach builds on a prior process comprehension framework for predicting…“Going on a vacation” takes longer than “Going for a walk”: A Study of Temporal Commonsense Understanding
Ben Zhou, Daniel Khashabi, Qiang Ning, Dan RothEMNLP • 2019 Understanding time is crucial for understanding events expressed in natural language. Because people rarely say the obvious, it is often necessary to have commonsense knowledge about various temporal aspects of events, such as duration, frequency, and…Pretrained Language Models for Sequential Sentence Classification
Arman Cohan, Iz Beltagy, Daniel King, Bhavana Dalvi, Daniel S. WeldEMNLP • 2019 As a step toward better document-level understanding, we explore classification of a sequence of sentences into their corresponding categories, a task that requires understanding sentences in context of the document. Recent successful models for this task…QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions
Oyvind Tafjord, Matt Gardner, Kevin Lin, Peter ClarkEMNLP • 2019 We introduce the first open-domain dataset, called QuaRTz, for reasoning about textual qualitative relationships. QuaRTz contains general qualitative statements, e.g., "A sunscreen with a higher SPF protects the skin longer.", twinned with 3864 crowdsourced…WIQA: A dataset for "What if..." reasoning over procedural text
Niket Tandon, Bhavana Dalvi Mishra, Keisuke Sakaguchi, Antoine Bosselut, Peter ClarkEMNLP • 2019 We introduce WIQA, the first large-scale dataset of "What if..." questions over procedural text. WIQA contains three parts: a collection of paragraphs each describing a process, e.g., beach erosion; a set of crowdsourced influence graphs for each paragraph…Exploiting Explicit Paths for Multi-hop Reading Comprehension
Souvik Kundu, Tushar Khot, Ashish Sabharwal, Peter ClarkACL • 2019 We propose a novel, path-based reasoning approach for the multi-hop reading comprehension task where a system needs to combine facts from multiple passages to answer a question. Although inspired by multi-hop reasoning over knowledge graphs, our proposed…Be Consistent! Improving Procedural Text Comprehension using Label Consistency
Xinya Du, Bhavana Dalvi Mishra, Niket Tandon, Antoine Bosselut, Wen-tau Yih, Peter Clark, Claire CardieNAACL-HLT • 2019 Our goal is procedural text comprehension, namely tracking how the properties of entities (e.g., their location) change with time given a procedural text (e.g., a paragraph about photosynthesis, a recipe). This task is challenging as the world is changing…Repurposing Entailment for Multi-Hop Question Answering Tasks
Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, Niranjan BalasubramanianNAACL • 2019 Question Answering (QA) naturally reduces to an entailment problem, namely, verifying whether some text entails the answer to a question. However, for multi-hop QA tasks, which require reasoning with multiple sentences, it remains unclear how best to utilize…Declarative Question Answering over Knowledge Bases containing Natural Language Text with Answer Set Programming
Arindam Mitra, Peter Clark, Oyvind Tafjord, Chitta BaralAAAI • 2019 While in recent years machine learning (ML) based approaches have been the popular approach in developing end-to-end question answering systems, such systems often struggle when additional knowledge is needed to correctly answer the questions. Proposed…