TA Chang, BK Bergen - Computational Linguistics, 2024 - direct.mit.edu
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 …
X Li, S Li, S Song, J Yang, J Ma, J Yu - Proceedings of the AAAI …, 2024 - ojs.aaai.org
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 …
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 …
L Yang, H Chen, Z Li, X Ding, X Wu - arXiv preprint arXiv:2306.11489, 2023 - arxiv.org
Recently, ChatGPT, a representative large language model (LLM), has gained considerable attention due to its powerful emergent abilities. Some researchers suggest that LLMs could …
We introduce a method for improving the structural understanding abilities of language models. Unlike previous approaches that finetune the models with task-specific …
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 …
S Kabir, DN Udo-Imeh, B Kou, T Zhang - arXiv preprint arXiv:2308.02312, 2023 - arxiv.org
Q&A platforms have been an integral part of the web-help-seeking behavior of programmers over the past decade. However, with the recent introduction of ChatGPT, the paradigm of …