Artificial General Intelligence (AGI) requires comprehensive understandi...
The convergence of text, visual, and audio data is a key step towards
hu...
Logical reasoning of text is an important ability that requires understa...
This paper focuses on analyzing and improving the commonsense ability of...
Answering open-domain questions requires world knowledge about in-contex...
Knowledge-intensive tasks, such as open-domain question answering (QA),
...
This paper revisits visual representation in knowledge-based visual ques...
Semi-supervised learning has shown promise in allowing NLP models to
gen...
Human intelligence is multimodal; we integrate visual, linguistic, and
a...
In peer review, reviewers are usually asked to provide scores for the pa...
Most of today's AI systems focus on using self-attention mechanisms and
...
Vision-and-language (VL) pre-training has proven to be highly effective ...
Commonsense reasoning (CSR) requires the model to be equipped with gener...
Pre-trained language models (PLMs) aim to learn universal language
repre...
Current Open-Domain Question Answering (ODQA) model paradigm often conta...
Commonsense reasoning requires a model to make presumptions about world
...
Preference-based Reinforcement Learning (PbRL) replaces reward values in...
We consider a novel setting of zeroth order non-convex optimization, whe...
Graph Neural Networks (GNNs) for prediction tasks like node classificati...
The Thresholding Bandit Problem (TBP) aims to find the set of arms with ...
This paper describes our competing system to enter the MEDIQA-2019
compe...
We propose a multi-task learning framework to jointly train a Machine Re...
We consider peer review in a conference setting where there is typically...
In supervised learning, we leverage a labeled dataset to design methods ...
This paper presents a new MRC model that is capable of three key
compreh...
We study the problem of interactively learning a binary classifier using...
Fine-grained classification is challenging because categories can only b...
Even though convolutional neural networks (CNN) has achieved near-human
...