Most of previous work on learning diacritization of the Arabic language
...
Motion forecasting for autonomous driving is a challenging task because
...
Rotation equivariance is a desirable property in many practical applicat...
Behavior prediction models have proliferated in recent years, especially...
As pre-trained language models have gotten larger, there has been growin...
Recently, mT5 - a massively multilingual version of T5 - leveraged a uni...
Most widely-used pre-trained language models operate on sequences of tok...
In this work, we explore "prompt tuning", a simple yet effective mechani...
Generating natural sentences from Knowledge Graph (KG) triples, known as...
The recent "Text-to-Text Transfer Transformer" (T5) leveraged a unified
...
We present LAReQA, a challenging new benchmark for language-agnostic ans...
Purely character-based language models (LMs) have been lagging in qualit...
Can neural networks learn to compare graphs without feature engineering?...
LSTMs and other RNN variants have shown strong performance on character-...
Graph embedding methods represent nodes in a continuous vector space,
pr...
We propose a new method for embedding graphs while preserving directed e...
This paper presents a computationally efficient machine-learned method f...
This paper presents the first attempt, up to our knowledge, to classify
...
Neural network based models are a very powerful tool for creating word
e...
The long-term memory of most connectionist systems lies entirely in the
...
We investigate the task of modeling open-domain, multi-turn, unstructure...
Theano is a Python library that allows to define, optimize, and evaluate...
We seek to better understand the difference in quality of the several
pu...