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- Publications
- Influence
AllenNLP: A Deep Semantic Natural Language Processing Platform
- Matt Gardner, Joel Grus, +6 authors Luke Zettlemoyer
- Computer Science
- ArXiv
- 20 March 2018
This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding. AllenNLP is designed to support researchers who want to build novel language… Expand
Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
- Peter Clark, Isaac Cowhey, +4 authors Oyvind Tafjord
- Computer Science
- ArXiv
- 14 March 2018
We present a new question set, text corpus, and baselines assembled to encourage AI research in advanced question answering. Together, these constitute the AI2 Reasoning Challenge (ARC), which… Expand
Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions
- Peter Clark, Oren Etzioni, +4 authors Daniel Khashabi
- Computer Science
- AAAI
- 12 February 2016
What capabilities are required for an AI system to pass standard 4th Grade Science Tests? Previous work has examined the use of Markov Logic Networks (MLNs) to represent the requisite background… Expand
Reasoning Over Paragraph Effects in Situations
- Kevin Lin, Oyvind Tafjord, Peter Clark, Matt Gardner
- Computer Science
- MRQA@EMNLP
- 16 August 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… Expand
Semantic Parsing to Probabilistic Programs for Situated Question Answering
- J. Krishnamurthy, Oyvind Tafjord, Aniruddha Kembhavi
- Computer Science
- EMNLP
- 22 June 2016
Situated question answering is the problem of answering questions about an environment such as an image or diagram. This problem requires jointly interpreting a question and an environment using… Expand
UnifiedQA: Crossing Format Boundaries With a Single QA System
- Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, P. Clark, Hannaneh Hajishirzi
- Computer Science
- ArXiv
- 2 May 2020
Question answering (QA) tasks have been posed using a variety of formats, such as extractive span selection, multiple choice, etc. This has led to format-specialized models, and even to an implicit… Expand
Transformers as Soft Reasoners over Language
- P. Clark, Oyvind Tafjord, Kyle Richardson
- Computer Science
- ArXiv
- 14 February 2020
Beginning with McCarthy's Advice Taker (1959), AI has pursued the goal of providing a system with explicit, general knowledge and having the system reason over that knowledge. However, expressing the… Expand
Moving beyond the Turing Test with the Allen AI Science Challenge
- Carissa Schoenick, Peter Clark, Oyvind Tafjord, Peter D. Turney, Oren Etzioni
- Computer Science
- Commun. ACM
- 14 April 2016
Answering questions correctly from standardized eighth-grade science tests is itself a test of machine intelligence.
QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships
- Oyvind Tafjord, P. Clark, Matt Gardner, Wen-tau Yih, A. Sabharwal
- Computer Science
- AAAI
- 20 November 2018
Many natural language questions require recognizing and reasoning with qualitative relationships (e.g., in science, economics, and medicine), but are challenging to answer with corpus-based methods.… Expand
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project
- P. Clark, Oren Etzioni, +11 authors M. Schmitz
- Computer Science
- ArXiv
- 4 September 2019
AI has achieved remarkable mastery over games such as Chess, Go, and Poker, and even Jeopardy, but the rich variety of standardized exams has remained a landmark challenge. Even in 2016, the best AI… Expand