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ERASER: A Benchmark to Evaluate Rationalized NLP Models
TLDR
This work proposes the Evaluating Rationales And Simple English Reasoning (ERASER) a benchmark to advance research on interpretable models in NLP, and proposes several metrics that aim to capture how well the rationales provided by models align with human rationales, and also how faithful these rationales are.
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Inferring Which Medical Treatments Work from Reports of Clinical Trials
TLDR
A new task and corpus for inferring reported findings from a full-text article describing randomized controlled trials (RCT) with respect to a given intervention, comparator, and outcome of interest and results using a suite of baseline models demonstrate the difficulty of the task.
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Neural-Network Lexical Translation for Cross-lingual IR from Text and Speech
We propose a neural network model to estimate word translation probabilities for Cross-Lingual Information Retrieval (CLIR). The model estimates better probabilities for word translations than…
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MSˆ2: Multi-Document Summarization of Medical Studies
TLDR
This work releases MSˆ2 (Multi-Document Summarization of Medical Studies), a dataset of over 470k documents and 20K summaries derived from the scientific literature that facilitates the development of systems that can assess and aggregate contradictory evidence across multiple studies, and is the first large-scale, publicly available multi-document summarization dataset in the biomedical domain.
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Evidence Inference 2.0: More Data, Better Models
TLDR
Additional annotations are collected to expand the Evidence Inference dataset by 25%, provide stronger baseline models, systematically inspect the errors that these make, and probe dataset quality.
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Twitter at the Grammys: A Social Media Corpus for Entity Linking and Disambiguation
TLDR
A new Twitter corpus that contains entity annotations for entity clusters that supports CDCR is introduced, drawing from Twitter data surrounding the 2013 Grammy music awards ceremony, providing a large set of annotated tweets focusing on a single event.
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Combining rule-based and statistical mechanisms for low-resource named entity recognition
We describe a multifaceted approach to named entity recognition that can be deployed with minimal data resources and a handful of hours of non-expert annotation. We describe how this approach was…
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PARMA: A Predicate Argument Aligner
We introduce PARMA, a system for crossdocument, semantic predicate and argument alignment. Our system combines a number of linguistic resources familiar to researchers in areas such as recognizing…
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Faster ( and Better ) Entity Linking with Cascades
TLDR
This work adapts the web-ranking prediction cascade learning algorithm, Cronus, in order to learn cascades that are both accurate and fast, and presents Slinky, a modular, flexible, fast and accurate entity linker based on prediction cascades.
Ambient temperature hydrophosphination of internal, unactivated alkynes and allenyl phosphineoxides with phosphine borane complexes.
Phosphine boranes have been found to hydrophosphinate internal, unactivated alkynes at room temperature under basic conditions without the need for catalysts or radical initiators. The use of…
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