1 |
Team PyKale (xy9) Submission to the EPIC-Kitchens 2021 Unsupervised Domain Adaptation Challenge for Action Recognition ...
|
|
|
|
BASE
|
|
Show details
|
|
2 |
Nutribullets Hybrid: Multi-document Health Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
3 |
Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment
|
|
|
|
In: MIT Press (2019)
|
|
BASE
|
|
Show details
|
|
5 |
Learning to refine text based recommendations
|
|
|
|
In: MIT web domain (2019)
|
|
BASE
|
|
Show details
|
|
6 |
Learning to refine text based recommendations
|
|
|
|
In: MIT web domain (2019)
|
|
BASE
|
|
Show details
|
|
7 |
Semi-supervised question retrieval with gated convolutions
|
|
|
|
In: arXiv (2016)
|
|
BASE
|
|
Show details
|
|
8 |
High-order low-rank tensors for semantic role labeling
|
|
|
|
In: MIT Web Domain (2015)
|
|
BASE
|
|
Show details
|
|
9 |
Molding CNNs for text: Non-linear, non-consecutive convolutions
|
|
|
|
In: MIT Web Domain (2015)
|
|
BASE
|
|
Show details
|
|
10 |
Low-Rank Tensors for Scoring Dependency Structures
|
|
|
|
In: MIT web domain (2014)
|
|
BASE
|
|
Show details
|
|
11 |
Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees
|
|
|
|
In: MIT web domain (2014)
|
|
BASE
|
|
Show details
|
|
12 |
From Natural Language Specifications to Program Input Parsers
|
|
|
|
In: MIT web domain (2013)
|
|
BASE
|
|
Show details
|
|
13 |
Learning High-Level Planning from Text
|
|
|
|
In: MIT web domain (2012)
|
|
BASE
|
|
Show details
|
|
|
|