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Do Abstractions Have Politics? Towards a More Critical Algorithm Analysis
The expansion of computer science (CS) education in K–12 and higher-educ...
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End-to-End Human Pose and Mesh Reconstruction with Transformers
We present a new method, called MEsh TRansfOrmer (METRO), to reconstruct...
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Nifty Web Apps: Build a Web App for Any Text-Based Programming Assignment
While many students now interact with web apps across a variety of smart...
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VIVO: Surpassing Human Performance in Novel Object Captioning with Visual Vocabulary Pre-Training
It is highly desirable yet challenging to generate image captions that c...
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A Berkeley View of Teaching CS at Scale
Over the past decade, undergraduate Computer Science (CS) programs acros...
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Evaluating NLP Models via Contrast Sets
Standard test sets for supervised learning evaluate in-distribution gene...
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Learning Nonparametric Human Mesh Reconstruction from a Single Image without Ground Truth Meshes
Nonparametric approaches have shown promising results on reconstructing ...
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Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers
Since hardware resources are limited, the objective of training deep lea...
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Learning to Generate Multiple Style Transfer Outputs for an Input Sentence
Text style transfer refers to the task of rephrasing a given text in a d...
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Neural Module Networks for Reasoning over Text
Answering compositional questions that require multiple steps of reasoni...
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QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions
We introduce the first open-domain dataset, called QuaRTz, for reasoning...
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Reasoning Over Paragraph Effects in Situations
A key component of successfully reading a passage of text is the ability...
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Cross-Domain Complementary Learning with Synthetic Data for Multi-Person Part Segmentation
The success of supervised deep learning depends on the training labels. ...
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Statistically and Computationally Efficient Change Point Localization in Regression Settings
Detecting when the underlying distribution changes from the observed tim...
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Grammar-based Neural Text-to-SQL Generation
The sequence-to-sequence paradigm employed by neural text-to-SQL models ...
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Subgoals, Problem Solving Phases, and Sources of Knowledge: A Complex Mangle
Educational researchers have increasingly drawn attention to how student...
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Covariance-based sample selection for heterogenous data: Applications to gene expression and autism risk gene detection
Risk for autism can be influenced by genetic mutations in hundreds of ge...
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Post-Selection Inference for Changepoint Detection Algorithms with Application to Copy Number Variation Data
Changepoint detection methods are used in many areas of science and engi...
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DeepBase: Deep Inspection of Neural Networks
Although deep learning models perform remarkably across a range of tasks...
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Adversarial Learning for Fine-grained Image Search
Fine-grained image search is still a challenging problem due to the diff...
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Adversarial Ranking for Language Generation
Generative adversarial networks (GANs) have great successes on synthesiz...
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Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks
This paper presents a simple yet effective supervised deep hash approach...
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Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification
In this paper we present two new approaches to efficiently solve large-s...
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