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Scalable Bottom-Up Hierarchical Clustering
Bottom-up algorithms such as the classic hierarchical agglomerative clus...
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Clustering-based Inference for Zero-Shot Biomedical Entity Linking
Due to large number of entities in biomedical knowledge bases, only a sm...
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Improving Local Identifiability in Probabilistic Box Embeddings
Geometric embeddings have recently received attention for their natural ...
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Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion
A case-based reasoning (CBR) system solves a new problem by retrieving `...
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Unsupervised Pre-training for Biomedical Question Answering
We explore the suitability of unsupervised representation learning metho...
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Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models
The discrepancy between maximum likelihood estimation (MLE) and task mea...
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Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks
Self-supervised pre-training of transformer models has revolutionized NL...
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A Simple Approach to Case-Based Reasoning in Knowledge Bases
We present a surprisingly simple yet accurate approach to reasoning in k...
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AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
Can one build a knowledge graph (KG) for all products in the world? Know...
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Using BibTeX to Automatically Generate Labeled Data for Citation Field Extraction
Accurate parsing of citation reference strings is crucial to automatical...
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ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning
Given questions regarding some prototypical situation – such as Name som...
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Compact Representation of Uncertainty in Hierarchical Clustering
Hierarchical clustering is a fundamental task often used to discover mea...
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Scalable Hierarchical Clustering with Tree Grafting
We introduce Grinch, a new algorithm for large-scale, non-greedy hierarc...
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Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision
Understanding the meaning of text often involves reasoning about entitie...
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Overcoming Practical Issues of Deep Active Learning and its Applications on Named Entity Recognition
Existing deep active learning algorithms achieve impressive sampling eff...
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Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks
Self-supervised pre-training of transformer models has shown enormous su...
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Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering
Multi-hop question answering (QA) requires an information retrieval (IR)...
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Optimal Transport-based Alignment of Learned Character Representations for String Similarity
String similarity models are vital for record linkage, entity resolution...
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Supervised Hierarchical Clustering with Exponential Linkage
In supervised clustering, standard techniques for learning a pairwise di...
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Energy and Policy Considerations for Deep Learning in NLP
Recent progress in hardware and methodology for training neural networks...
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Paper Matching with Local Fairness Constraints
Automatically matching reviewers to papers is a crucial step of the peer...
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The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures
Materials science literature contains millions of materials synthesis pr...
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Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
This paper introduces a new framework for open-domain question answering...
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OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference
In this paper, we consider advancing web-scale knowledge extraction and ...
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Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders
We introduce deep inside-outside recursive autoencoders (DIORA), a fully...
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Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks
Leveraging new data sources is a key step in accelerating the pace of ma...
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Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks
In structured output prediction tasks, labeling ground-truth training ou...
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Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?
Do unsupervised methods for learning rich, contextualized token represen...
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Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
We propose a neural machine-reading model that constructs dynamic knowle...
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Embedded-State Latent Conditional Random Fields for Sequence Labeling
Complex textual information extraction tasks are often posed as sequence...
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Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking
Extraction from raw text to a knowledge base of entities and fine-graine...
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A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset
The recent work of Clark et al. introduces the AI2 Reasoning Challenge (...
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Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures
Embedding methods which enforce a partial order or lattice structure ove...
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Linguistically-Informed Self-Attention for Semantic Role Labeling
The current state-of-the-art end-to-end semantic role labeling (SRL) mod...
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Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings
Word sense induction (WSI), which addresses polysemy by unsupervised dis...
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Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction
Most work in relation extraction forms a prediction by looking at a shor...
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Automatically Extracting Action Graphs from Materials Science Synthesis Procedures
Computational synthesis planning approaches have achieved recent success...
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Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
Knowledge bases (KB), both automatically and manually constructed, are o...
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Finer Grained Entity Typing with TypeNet
We consider the challenging problem of entity typing over an extremely f...
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Attending to All Mention Pairs for Full Abstract Biological Relation Extraction
Most work in relation extraction forms a prediction by looking at a shor...
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Unsupervised Hypernym Detection by Distributional Inclusion Vector Embedding
Modeling hypernymy, such as poodle is-a dog, is an important generalizat...
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Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling
In textual information extraction and other sequence labeling tasks it i...
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Improved Representation Learning for Predicting Commonsense Ontologies
Recent work in learning ontologies (hierarchical and partially-ordered s...
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RelNet: End-to-End Modeling of Entities & Relations
We introduce RelNet: a new model for relational reasoning. RelNet is a m...
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Dependency Parsing with Dilated Iterated Graph CNNs
Dependency parses are an effective way to inject linguistic knowledge in...
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Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks
Existing question answering methods infer answers either from a knowledg...
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Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples
Self-paced learning and hard example mining re-weight training instances...
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SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications
We describe the SemEval task of extracting keyphrases and relations betw...
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An Online Hierarchical Algorithm for Extreme Clustering
Many modern clustering methods scale well to a large number of data item...
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End-to-End Learning for Structured Prediction Energy Networks
Structured Prediction Energy Networks (SPENs) are a simple, yet expressi...
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