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PDDL-the planning domain definition language
TLDR
This manual describes the syntax of PDDL, the Planning Domain Definition Language, the problem-specification language for the AIPS-98 planning competition, and hopes to encourage empirical evaluation of planner performance, and development of standard sets of problems all in comparable notations.
TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
TLDR
It is shown that, in comparison to other recently introduced large-scale datasets, TriviaQA has relatively complex, compositional questions, has considerable syntactic and lexical variability between questions and corresponding answer-evidence sentences, and requires more cross sentence reasoning to find answers.
SpanBERT: Improving Pre-training by Representing and Predicting Spans
TLDR
The approach extends BERT by masking contiguous random spans, rather than random tokens, and training the span boundary representations to predict the entire content of the masked span, without relying on the individual token representations within it.
Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations
TLDR
A novel approach for multi-instance learning with overlapping relations that combines a sentence-level extraction model with a simple, corpus-level component for aggregating the individual facts is presented.
Fine-Grained Entity Recognition
TLDR
A fine-grained set of 112 tags is defined, the tagging problem is formulates as multi-class, multi-label classification, an unsupervised method for collecting training data is described, and the FIGER implementation is presented.
UCPOP: A Sound, Complete, Partial Order Planner for ADL
TLDR
It is proved ucpop is both sound and complete for this representation and a practical implementation that succeeds on all of Pednault's and McDermott's examples, including the infamous "Yale Stacking Problem".
An Introduction to Least Commitment Planning
TLDR
A progression of least commitment planners is summarized, starting with one that handles the simple STRIPS representation and ending with UCPOP, a planner that manages actions with disjunctive precondition, conditional effects, and universal quantification over dynamic universes.
Web-scale information extraction in knowitall: (preliminary results)
TLDR
KnowItAll, a system that aims to automate the tedious process of extracting large collections of facts from the web in an autonomous, domain-independent, and scalable manner, is introduced.
CORD-19: The COVID-19 Open Research Dataset
TLDR
The mechanics of dataset construction are described, highlighting challenges and key design decisions, an overview of how CORD-19 has been used, and several shared tasks built around the dataset are described.
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