Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …

Pre-trained Language Models (PLMs) which are trained on large text corpus via self-
supervised learning method, have yielded promising performance on various tasks in …

Large-scale language models are rapidly improving, performing well on a wide variety of
tasks with little to no customization. In this work we investigate how language models can …

Commonsense reasoning aims to empower machines with the human ability to make
presumptions about ordinary situations in our daily life. In this paper, we propose a textual …

We present the first comprehensive study on automatic knowledge base construction for two
prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet …

One of the most challenging question types in VQA is when answering the question requires
outside knowledge not present in the image. In this work we study open-domain knowledge …

Given a partial description like" she opened the hood of the car," humans can reason about
the situation and anticipate what might come next (" then, she examined the engine"). In this …

Recently, large-scale pre-trained language models have demonstrated impressive
performance on several commonsense-reasoning benchmark datasets. However, building …

Inferring commonsense knowledge is a key challenge in machine learning. Due to the
sparsity of training data, previous work has shown that supervised methods for …