b'Kevin Lin'

research

∙ 06/14/2022

LAVENDER: Unifying Video-Language Understanding as Masked Language Modeling

Unified vision-language frameworks have greatly advanced in recent years...

Linjie Li, et al. ∙

research

∙ 05/27/2022

GIT: A Generative Image-to-text Transformer for Vision and Language

In this paper, we design and train a Generative Image-to-text Transforme...

Jianfeng Wang, et al. ∙

research

∙ 05/03/2022

Cross-modal Representation Learning for Zero-shot Action Recognition

We present a cross-modal Transformer-based framework, which jointly enco...

Chung-Ching Lin, et al. ∙

research

∙ 12/07/2021

Combining optimal control and learning for autonomous aerial navigation in novel indoor environments

This report proposes a combined optimal control and perception framework...

Kevin Lin, et al. ∙

research

∙ 11/25/2021

SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning

The canonical approach to video captioning dictates a caption generation...

Kevin Lin, et al. ∙

research

∙ 11/24/2021

VIOLET : End-to-End Video-Language Transformers with Masked Visual-token Modeling

A great challenge in video-language (VidL) modeling lies in the disconne...

Tsu-Jui Fu, et al. ∙

research

∙ 09/27/2021

CS Education for the Socially-Just Worlds We Need: The Case for Justice-Centered Approaches to CS in Higher Education

Justice-centered approaches to equitable computer science (CS) education...

Kevin Lin, et al. ∙

research

∙ 08/08/2021

OVIS: Open-Vocabulary Visual Instance Search via Visual-Semantic Aligned Representation Learning

We introduce the task of open-vocabulary visual instance search (OVIS). ...

Sheng Liu, et al. ∙

research

∙ 04/01/2021

Mesh Graphormer

We present a graph-convolution-reinforced transformer, named Mesh Grapho...

Kevin Lin, et al. ∙

research

∙ 01/04/2021

Do Abstractions Have Politics? Towards a More Critical Algorithm Analysis

The expansion of computer science (CS) education in K–12 and higher-educ...

Kevin Lin, et al. ∙

research

∙ 12/17/2020

End-to-End Human Pose and Mesh Reconstruction with Transformers

We present a new method, called MEsh TRansfOrmer (METRO), to reconstruct...

Kevin Lin, et al. ∙

research

∙ 10/09/2020

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...

Kevin Lin, et al. ∙

research

∙ 09/28/2020

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...

Xiaowei Hu, et al. ∙

research

∙ 04/28/2020

A Berkeley View of Teaching CS at Scale

Over the past decade, undergraduate Computer Science (CS) programs acros...

Kevin Lin, et al. ∙

research

∙ 04/06/2020

Evaluating NLP Models via Contrast Sets

Standard test sets for supervised learning evaluate in-distribution gene...

Matt Gardner, et al. ∙

research

∙ 02/28/2020

Learning Nonparametric Human Mesh Reconstruction from a Single Image without Ground Truth Meshes

Nonparametric approaches have shown promising results on reconstructing ...

Kevin Lin, et al. ∙

research

∙ 02/26/2020

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...

Zhuohan Li, et al. ∙

research

∙ 02/16/2020

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...

Kevin Lin, et al. ∙

research

∙ 12/10/2019

Neural Module Networks for Reasoning over Text

Answering compositional questions that require multiple steps of reasoni...

Nitish Gupta, et al. ∙

research

∙ 09/08/2019

QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions

We introduce the first open-domain dataset, called QuaRTz, for reasoning...

Oyvind Tafjord, et al. ∙

research

∙ 08/16/2019

Reasoning Over Paragraph Effects in Situations

A key component of successfully reading a passage of text is the ability...

Kevin Lin, et al. ∙

research

∙ 07/11/2019

Cross-Domain Complementary Learning with Synthetic Data for Multi-Person Part Segmentation

The success of supervised deep learning depends on the training labels. ...

Kevin Lin, et al. ∙

research

∙ 06/26/2019

Statistically and Computationally Efficient Change Point Localization in Regression Settings

Detecting when the underlying distribution changes from the observed tim...

Daren Wang, et al. ∙

research

∙ 05/30/2019

Grammar-based Neural Text-to-SQL Generation

The sequence-to-sequence paradigm employed by neural text-to-SQL models ...

Kevin Lin, et al. ∙

research

∙ 01/05/2019

Subgoals, Problem Solving Phases, and Sources of Knowledge: A Complex Mangle

Educational researchers have increasingly drawn attention to how student...

Kevin Lin, et al. ∙

research

∙ 12/19/2018

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...

Kevin Lin, et al. ∙

research

∙ 12/10/2018

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...

Sangwon Hyun, et al. ∙

research

∙ 08/13/2018

DeepBase: Deep Inspection of Neural Networks

Although deep learning models perform remarkably across a range of tasks...

Thibault Sellam, et al. ∙

research

∙ 07/06/2018

Adversarial Learning for Fine-grained Image Search

Fine-grained image search is still a challenging problem due to the diff...

Kevin Lin, et al. ∙

research

∙ 05/31/2017

Adversarial Ranking for Language Generation

Generative adversarial networks (GANs) have great successes on synthesiz...

Kevin Lin, et al. ∙

research

∙ 07/01/2015

Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks

This paper presents a simple yet effective supervised deep hash approach...

Huei-Fang Yang, et al. ∙

research

∙ 12/16/2013

Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification

In this paper we present two new approaches to efficiently solve large-s...

Robert Vanderbei, et al. ∙

Kevin Lin

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