Large, pre-trained language models (PLMs) such as BERT and GPT have drastically
changed the Natural Language Processing (NLP) field. For numerous NLP tasks …

This article surveys and organizes research works in a new paradigm in natural language
processing, which we dub “prompt-based learning.” Unlike traditional supervised learning …

Recently, prompt tuning has been widely applied to stimulate the rich knowledge in pre-
trained language models (PLMs) to serve NLP tasks. Although prompt tuning has achieved …

This paper presents an exhaustive quantitative and qualitative evaluation of Large
Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We …

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 …

Multimodal Knowledge Graphs (MKGs), which organize visual-text factual knowledge, have
recently been successfully applied to tasks such as information retrieval, question …

Prompt engineering is a technique that involves augmenting a large pre-trained model with
task-specific hints, known as prompts, to adapt the model to new tasks. Prompts can be …

Large language models (LLMs) have significantly advanced the field of natural language
processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of …

Multimodal named entity recognition and relation extraction (MNER and MRE) is a
fundamental and crucial branch in information extraction. However, existing approaches for …

Bug reports are vital for software maintenance that allow users to inform developers of the
problems encountered while using the software. As such, researchers have committed …