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Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
We present the Open Predicate Query Language (OPQL); a method for constr...
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Evaluating Explanations: How much do explanations from the teacher aid students?
While many methods purport to explain predictions by highlighting salien...
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Open Question Answering over Tables and Text
In open question answering (QA), the answer to a question is produced by...
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Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge
Massive language models are the core of modern NLP modeling and have bee...
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Guessing What's Plausible But Remembering What's True: Accurate Neural Reasoning for Question-Answering
Neural approaches to natural language processing (NLP) often fail at the...
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Differentiable Reasoning over a Virtual Knowledge Base
We consider the task of answering complex multi-hop questions using a co...
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Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base
We describe a novel way of representing a symbolic knowledge base (KB) c...
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Game Design for Eliciting Distinguishable Behavior
The ability to inferring latent psychological traits from human behavior...
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Instance-based Transfer Learning for Multilingual Deep Retrieval
Perhaps the simplest type of multilingual transfer learning is instance-...
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PubMedQA: A Dataset for Biomedical Research Question Answering
We introduce PubMedQA, a novel biomedical question answering (QA) datase...
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Handling Divergent Reference Texts when Evaluating Table-to-Text Generation
Automatically constructed datasets for generating text from semi-structu...
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Differentiable Representations For Multihop Inference Rules
We present efficient differentiable implementations of second-order mult...
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Neural Query Language: A Knowledge Base Query Language for Tensorflow
Large knowledge bases (KBs) are useful for many AI tasks, but are diffic...
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PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text
We consider open-domain queston answering (QA) where answers are drawn f...
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Probing Biomedical Embeddings from Language Models
Contextualized word embeddings derived from pre-trained language models ...
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Incremental Reading for Question Answering
Any system which performs goal-directed continual learning must not only...
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Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
Transformer networks have a potential of learning longer-term dependency...
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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Existing question answering (QA) datasets fail to train QA systems to pe...
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Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text
Open Domain Question Answering (QA) is evolving from complex pipelined s...
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GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations
Modern deep transfer learning approaches have mainly focused on learning...
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Semi-Supervised Learning with Declaratively Specified Entropy Constraints
We propose a technique for declaratively specifying strategies for semi-...
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Neural Models for Reasoning over Multiple Mentions using Coreference
Many problems in NLP require aggregating information from multiple menti...
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Learning to Organize Knowledge with N-Gram Machines
Deep neural networks (DNNs) had great success on NLP tasks such as langu...
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Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
We formulate language modeling as a matrix factorization problem, and sh...
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TensorLog: Deep Learning Meets Probabilistic DBs
We present an implementation of a probabilistic first-order logic called...
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Quasar: Datasets for Question Answering by Search and Reading
We present two new large-scale datasets aimed at evaluating systems desi...
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Good Semi-supervised Learning that Requires a Bad GAN
Semi-supervised learning methods based on generative adversarial network...
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Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks
Recent papers have shown that neural networks obtain state-of-the-art pe...
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Linguistic Knowledge as Memory for Recurrent Neural Networks
Training recurrent neural networks to model long term dependencies is di...
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Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning
We propose a general approach to modeling semi-supervised learning (SSL)...
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A Comparative Study of Word Embeddings for Reading Comprehension
The focus of past machine learning research for Reading Comprehension ta...
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Differentiable Learning of Logical Rules for Knowledge Base Reasoning
We study the problem of learning probabilistic first-order logical rules...
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Semi-Supervised QA with Generative Domain-Adaptive Nets
We study the problem of semi-supervised question answering----utilizing ...
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Words or Characters? Fine-grained Gating for Reading Comprehension
Previous work combines word-level and character-level representations us...
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Bootstrapping Distantly Supervised IE using Joint Learning and Small Well-structured Corpora
We propose a framework to improve performance of distantly-supervised re...
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Gated-Attention Readers for Text Comprehension
In this paper we study the problem of answering cloze-style questions ov...
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Review Networks for Caption Generation
We propose a novel extension of the encoder-decoder framework, called a ...
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Tweet2Vec: Character-Based Distributed Representations for Social Media
Text from social media provides a set of challenges that can cause tradi...
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Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams
Early detection and precise characterization of emerging topics in text ...
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Distant IE by Bootstrapping Using Lists and Document Structure
Distant labeling for information extraction (IE) suffers from noisy trai...
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Grounded Discovery of Coordinate Term Relationships between Software Entities
We present an approach for the detection of coordinate-term relationship...
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Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic
One important challenge for probabilistic logics is reasoning with very ...
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The Effect of Biased Communications On Both Trusting and Suspicious Voters
In recent studies of political decision-making, apparently anomalous beh...
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Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic
In many probabilistic first-order representation systems, inference is p...
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