Give us the facts: Enhancing large language models with knowledge graphs for fact-aware language modeling

L Yang, H Chen, Z Li, X Ding… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Recently, ChatGPT, a representative large language model (LLM), has gained considerable
attention. Due to their powerful emergent abilities, recent LLMs are considered as a possible …

Datasets for large language models: A comprehensive survey

Y Liu, J Cao, C Liu, K Ding, L ** - arxiv preprint arxiv:2402.18041, 2024 - arxiv.org
This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …

[PDF][PDF] Language model behavior: A comprehensive survey

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 …

ROBBIE: Robust bias evaluation of large generative language models

D Esiobu, X Tan, S Hosseini, M Ung, Y Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
As generative large language models (LLMs) grow more performant and prevalent, we must
develop comprehensive enough tools to measure and improve their fairness. Different …

Evaluating large language models in theory of mind tasks

M Kosinski - Proceedings of the National Academy of Sciences, 2024 - pnas.org
Eleven large language models (LLMs) were assessed using 40 bespoke false-belief tasks,
considered a gold standard in testing theory of mind (ToM) in humans. Each task included a …

A causal explainable guardrails for large language models

Z Chu, Y Wang, L Li, Z Wang, Z Qin, K Ren - Proceedings of the 2024 on …, 2024 - dl.acm.org
Large Language Models (LLMs) have shown impressive performance in natural language
tasks, but their outputs can exhibit undesirable attributes or biases. Existing methods for …

Adversarial Attacks on Large Language Model‐Based System and Mitigating Strategies: A Case Study on ChatGPT

B Liu, B **ao, X Jiang, S Cen, X He… - Security and …, 2023 - Wiley Online Library
Machine learning algorithms are at the forefront of the development of advanced information
systems. The rapid progress in machine learning technology has enabled cutting‐edge …

Give me the facts! a survey on factual knowledge probing in pre-trained language models

P Youssef, OA Koraş, M Li, J Schlötterer… - arxiv preprint arxiv …, 2023 - arxiv.org
Pre-trained Language Models (PLMs) are trained on vast unlabeled data, rich in world
knowledge. This fact has sparked the interest of the community in quantifying the amount of …

The life cycle of knowledge in big language models: A survey

B Cao, H Lin, X Han, L Sun - Machine Intelligence Research, 2024 - Springer
Abstract Knowledge plays a critical role in artificial intelligence. Recently, the extensive
success of pre-trained language models (PLMs) has raised significant attention about how …

Aligning as debiasing: Causality-aware alignment via reinforcement learning with interventional feedback

Y **a, T Yu, Z He, H Zhao, J McAuley… - Proceedings of the 2024 …, 2024 - aclanthology.org
Large language models (LLMs) often generate biased outputs containing offensive, toxic, or
stereotypical text. Existing LLM alignment methods such as reinforcement learning from …