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01/28/2023
ACL-Fig: A Dataset for Scientific Figure Classification
Most existing large-scale academic search engines are built to retrieve ...
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01/21/2022
SciBERTSUM: Extractive Summarization for Scientific Documents
The summarization literature focuses on the summarization of news articl...
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12/23/2021
A Synthetic Prediction Market for Estimating Confidence in Published Work
Explainably estimating confidence in published scholarly work offers opp...
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10/22/2021
SciCap: Generating Captions for Scientific Figures
Researchers use figures to communicate rich, complex information in scie...
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05/20/2021
Document Domain Randomization for Deep Learning Document Layout Extraction
We present document domain randomization (DDR), the first successful tra...
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04/08/2021
Predicting the Reproducibility of Social and Behavioral Science Papers Using Supervised Learning Models
In recent years, significant effort has been invested verifying the repr...
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04/07/2021
Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units
Automated mathematical reasoning is a challenging problem that requires ...
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01/05/2021
Design and Analysis of a Synthetic Prediction Market using Dynamic Convex Sets
We present a synthetic prediction market whose agent purchase logic is d...
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12/09/2020
Automating Document Classification with Distant Supervision to Increase the Efficiency of Systematic Reviews
Objective: Systematic reviews of scholarly documents often provide compl...
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12/07/2020
Modeling Updates of Scholarly Webpages Using Archived Data
The vastness of the web imposes a prohibitive cost on building large-sca...
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07/27/2020
Large Scale Subject Category Classification of Scholarly Papers with Deep Attentive Neural Networks
Subject categories of scholarly papers generally refer to the knowledge ...
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05/05/2020
CODA-19: Reliably Annotating Research Aspects on 10,000+ CORD-19 Abstracts Using a Non-Expert Crowd
This paper introduces CODA-19, a human-annotated dataset that codes the ...
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05/05/2020
CODA-19: Reliably Annotating Research Aspects on 10,000+ CORD-19 Abstracts Using Non-Expert Crowd
This paper introduces CODA-19, a human-annotated dataset that denotes th...
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04/23/2020
Privacy at Scale: Introducing the PrivaSeer Corpus of Web Privacy Policies
Organisations disclose their privacy practices by posting privacy polici...
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02/10/2020
Reducing the Computational Burden of Deep Learning with Recursive Local Representation Alignment
Training deep neural networks on large-scale datasets requires significa...
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12/09/2019
Query Auto Completion for Math Formula Search
Query Auto Completion (QAC) is among the most appealing features of a we...
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11/27/2019
Automatic Generation of Headlines for Online Math Questions
Mathematical equations are an important part of dissemination and commun...
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11/12/2019
Connecting First and Second Order Recurrent Networks with Deterministic Finite Automata
We propose an approach that connects recurrent networks with different o...
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10/15/2019
Shapley Homology: Topological Analysis of Sample Influence for Neural Networks
Data samples collected for training machine learning models are typicall...
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09/07/2019
The Neural State Pushdown Automata
In order to learn complex grammars, recurrent neural networks (RNNs) req...
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06/20/2019
Cleaning Noisy and Heterogeneous Metadata for Record Linking Across Scholarly Big Datasets
Automatically extracted metadata from scholarly documents in PDF formats...
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05/25/2019
Lifelong Neural Predictive Coding: Sparsity Yields Less Forgetting when Learning Cumulatively
In lifelong learning systems, especially those based on artificial neura...
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11/14/2018
Verification of Recurrent Neural Networks Through Rule Extraction
The verification problem for neural networks is verifying whether a neur...
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10/17/2018
Online Learning of Recurrent Neural Architectures by Locally Aligning Distributed Representations
Temporal models based on recurrent neural networks have proven to be qui...
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10/17/2018
Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations
Temporal models based on recurrent neural networks have proven to be qui...
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09/09/2018
TextContourNet: a Flexible and Effective Framework for Improving Scene Text Detection Architecture with a Multi-task Cascade
We study the problem of extracting text instance contour information fro...
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09/09/2018
A Neural Temporal Model for Human Motion Prediction
We propose novel neural temporal models for short-term motion prediction...
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04/23/2018
Guided Attention for Large Scale Scene Text Verification
Many tasks are related to determining if a particular text string exists...
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03/15/2018
Learned Iterative Decoding for Lossy Image Compression Systems
For lossy image compression systems, we develop an algorithm called iter...
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03/05/2018
Conducting Credit Assignment by Aligning Local Representations
The use of back-propagation and its variants to train deep networks is o...
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01/19/2018
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations
Strict partial order is a mathematical structure commonly seen in relati...
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01/16/2018
A Comparison of Rule Extraction for Different Recurrent Neural Network Models and Grammatical Complexity
It has been shown that rules can be extracted from highly non-linear, re...
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01/04/2018
Text Extraction and Retrieval from Smartphone Screenshots: Building a Repository for Life in Media
Daily engagement in life experiences is increasingly interwoven with mob...
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11/30/2017
Learning to Adapt by Minimizing Discrepancy
We explore whether useful temporal neural generative models can be learn...
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09/27/2017
Scaling Author Name Disambiguation with CNF Blocking
An author name disambiguation (AND) algorithm identifies a unique author...
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06/07/2017
Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Network
We present an end-to-end, multimodal, fully convolutional network for ex...
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05/17/2017
Learning a Hierarchical Latent-Variable Model of 3D Shapes
We propose the Variational Shape Learner (VSL), a hierarchical latent-va...
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11/22/2016
Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading
Physical library collections are valuable and long standing resources fo...
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01/26/2016
Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization
Many previous proposals for adversarial training of deep neural nets hav...
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01/16/2013
Bayesian Classification and Feature Selection from Finite Data Sets
Feature selection aims to select the smallest subset of features for a s...
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12/12/2012