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MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
TLDR
A large-scale dataset of math word problems and an interpretable neural math problem solver by learning to map problems to their operation programs and a new representation language to model operation programs corresponding to each math problem that aim to improve both the performance and the interpretability of the learned models.
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MAWPS: A Math Word Problem Repository
TLDR
MAWPS allows for the automatic construction of datasets with particular characteristics, providing tools for tuning the lexical and template overlap of a dataset as well as for filtering ungrammatical problems from web-sourced corpora.
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Extracting a Knowledge Base of Mechanisms from COVID-19 Papers
TLDR
This work pursues the construction of a knowledge base of mechanisms—a fundamental concept across the sciences, which encompasses activities, functions and causal relations, ranging from cellular processes to economic impacts, by developing a broad, unified schema.
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Procedural Reading Comprehension with Attribute-Aware Context Flow
TLDR
An algorithm for procedural reading comprehension is introduced by translating the text into a general formalism that represents processes as a sequence of transitions over entity attributes (e.g., location, temperature).
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Expressing Coherent Personality with Incremental Acquisition of Multimodal Behaviors
TLDR
An architecture that acquires dialog through crowdsourcing to author both verbal and non-verbal indicators of personality is extended and is able to elicit personality-driven language behaviors from the crowd in an incremental and ongoing way.
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Cross-lingual Subjectivity Detection for Resource Lean Languages
TLDR
Cross-lingual subjectivity detection on resource lean languages is investigated using two different approaches: a language-model based and a learning-to-rank approach that outperforms the baseline method in ranking documents based on their subjectivity degree.
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Dialog Inpainting: Turning Documents into Dialogs
TLDR
dial inpainting takes the text of any document and transforms it into a two- person dialog between the writer and an imagined reader, and uses a dialog inpainter to predict what the imagined reader asked or said in between each of the writer's utterances.
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Application of Natural Language Processing Toward Scientific Text Understanding
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Machine Learning Winter 2018 Lecture 17 : Reinforcement Learning , Finite Markov Decision Processes
TLDR
This section forms finite MDPs and introduces several solutions based on dynamic programming, which aim at maximizing the total rewards, or equivalently minimizing the regret, by deciding the action every time step.
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