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AllenNLP: A Deep Semantic Natural Language Processing Platform
AllenNLP is designed to support researchers who want to build novel language understanding models quickly and easily and provides a flexible data API that handles intelligent batching and padding, and a modular and extensible experiment framework that makes doing good science easy. Expand
Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
A new question set, text corpus, and baselines assembled to encourage AI research in advanced question answering constitute the AI2 Reasoning Challenge (ARC), which requires far more powerful knowledge and reasoning than previous challenges such as SQuAD or SNLI. Expand
UnifiedQA: Crossing Format Boundaries With a Single QA System
This work uses the latest advances in language modeling to build a single pre-trained QA model, UNIFIEDQA, that performs well across 19 QA datasets spanning 4 diverse formats, and results in a new state of the art on 10 factoid and commonsense question answering datasets. Expand
SUSY and Goliath
We investigate the ``giant gravitons'' of McGreevy, Susskind and Toumbas [1]. We demonstrate that these are BPS configurations which preserve precisely the same supersymmetries as a ``point-like''Expand
Superstars and giant gravitons
We examine a family of BPS solutions of ten-dimensional type-IIB supergravity. These solutions asymptotically approach AdS5 × S5 and carry internal `angular' momentum on the five-sphere. While aExpand
The Noncommutative bion core
We examine noncommutative solutions of the non-Abelian theory on the world-volume of N coincident D-strings. These solutions can be interpreted in terms of noncommutative geometry as funnelsExpand
Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions
This paper evaluates the methods on six years of unseen, unedited exam questions from the NY Regents Science Exam, and shows that the overall system's score is 71.3%, an improvement of 23.8% (absolute) over the MLN-based method described in previous work. Expand
Transformers as Soft Reasoners over Language
This work trains transformers to reason (or emulate reasoning) over natural language sentences using synthetically generated data, thus bypassing a formal representation and suggesting a new role for transformers, namely as limited "soft theorem provers" operating over explicit theories in language. Expand
Reasoning Over Paragraph Effects in Situations
This work presents ROPES, a challenging benchmark for reading comprehension targeting Reasoning Over Paragraph Effects in Situations, and targets expository language describing causes and effects, as they have clear implications for new situations. Expand
Non-abelian Brane Intersections
We study new solutions of the low-energy equations of motion for the non-abelian D-string. We find a "fuzzy funnel" solution consisting of a noncommutative four-sphere geometry which expands alongExpand