A survey on evaluation of large language models

Y Chang, X Wang, J Wang, Y Wu, L Yang… - ACM Transactions on …, 2024 - dl.acm.org
Large language models (LLMs) are gaining increasing popularity in both academia and
industry, owing to their unprecedented performance in various applications. As LLMs …

Large ai models in health informatics: Applications, challenges, and the future

J Qiu, L Li, J Sun, J Peng, P Shi… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Large AI models, or foundation models, are models recently emerging with massive scales
both parameter-wise and data-wise, the magnitudes of which can reach beyond billions …

[HTML][HTML] ChatGPT: Jack of all trades, master of none

J Kocoń, I Cichecki, O Kaszyca, M Kochanek, D Szydło… - Information …, 2023 - Elsevier
OpenAI has released the Chat Generative Pre-trained Transformer (ChatGPT) and
revolutionized the approach in artificial intelligence to human-model interaction. The first …

Harnessing the power of llms in practice: A survey on chatgpt and beyond

J Yang, H Jin, R Tang, X Han, Q Feng, H Jiang… - ACM Transactions on …, 2024 - dl.acm.org
This article presents a comprehensive and practical guide for practitioners and end-users
working with Large Language Models (LLMs) in their downstream Natural Language …

Unifying large language models and knowledge graphs: A roadmap

S Pan, L Luo, Y Wang, C Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
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 …

[HTML][HTML] Unlocking the opportunities through ChatGPT Tool towards ameliorating the education system

M Javaid, A Haleem, RP Singh, S Khan… - BenchCouncil …, 2023 - Elsevier
Abstract Artificial Intelligence (AI)-based ChatGPT developed by OpenAI is now widely
accepted in several fields, including education. Students can learn about ideas and theories …

Exploring the potential of large language models (llms) in learning on graphs

Z Chen, H Mao, H Li, W Jin, H Wen, X Wei… - ACM SIGKDD …, 2024 - dl.acm.org
Learning on Graphs has attracted immense attention due to its wide real-world applications.
The most popular pipeline for learning on graphs with textual node attributes primarily relies …

Trustworthy llms: a survey and guideline for evaluating large language models' alignment

Y Liu, Y Yao, JF Ton, X Zhang, R Guo, H Cheng… - arXiv preprint arXiv …, 2023 - arxiv.org
Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …

[PDF][PDF] DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models.

B Wang, W Chen, H Pei, C Xie, M Kang, C Zhang, C Xu… - NeurIPS, 2023 - blogs.qub.ac.uk
Abstract Generative Pre-trained Transformer (GPT) models have exhibited exciting progress
in their capabilities, capturing the interest of practitioners and the public alike. Yet, while the …

Promptbench: Towards evaluating the robustness of large language models on adversarial prompts

K Zhu, J Wang, J Zhou, Z Wang, H Chen… - arXiv preprint arXiv …, 2023 - arxiv.org
The increasing reliance on Large Language Models (LLMs) across academia and industry
necessitates a comprehensive understanding of their robustness to prompts. In response to …