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 language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

The common practice for training commonsense models has gone from-human-to-corpus-to-
machine: humans author commonsense knowledge graphs in order to train commonsense …

Storytelling and narrative are fundamental to human experience, intertwined with our social
and cultural engagement. As such, researchers have long attempted to create systems that …

Abstract Knowledge-based visual question answering (VQA) involves questions that require
world knowledge beyond the image to yield the correct answer. Large language models …

Knowledge-based visual question answering (VQA) involves questions that require world
knowledge beyond the image to yield the correct answer. Large language models (LMs) like …

Event extraction requires high-quality expert human annotations, which are usually
expensive. Therefore, learning a data-efficient event extraction model that can be trained …

Structured knowledge is important for many AI applications. Commonsense knowledge,
which is crucial for robust human-centric AI, is covered by a small number of structured …

Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …

In recent years, researchers attempt to utilize online social information to alleviate data
sparsity for collaborative filtering, based on the rationale that social networks offers the …