Pre-trained language models (PLMs) have been the de facto paradigm for most natural
language processing tasks. This also benefits the biomedical domain: researchers from …

Transformer language models have received widespread public attention, yet their
generated text is often surprising even to NLP researchers. In this survey, we discuss over …

Despite their impressive performance on diverse tasks, large language models (LMs) still
struggle with tasks requiring rich world knowledge, implying the limitations of relying solely …

Previous studies have shown that large language models (LLMs) like GPTs store massive
factual knowledge in their parameters. However, the stored knowledge could be false or out …

Model editing techniques modify a minor proportion of knowledge in Large Language
Models (LLMs) at a relatively low cost, which have demonstrated notable success. Existing …

Recently, ChatGPT, a representative large language model (LLM), has gained considerable
attention due to its powerful emergent abilities. Some researchers suggest that LLMs could …

Large Language Models (LLMs) have taken Knowledge Representation--and the world--by
storm. This inflection point marks a shift from explicit knowledge representation to a renewed …

Previous literature has proved that Pretrained Language Models (PLMs) can store factual
knowledge. However, we find that facts stored in the PLMs are not always correct. It …

Q&A platforms have been crucial for the online help-seeking behavior of programmers.
However, the recent popularity of ChatGPT is altering this trend. Despite this popularity, no …

We introduce a method for improving the structural understanding abilities of language
models. Unlike previous approaches that finetune the models with task-specific …