Combating misinformation in the age of llms: Opportunities and challenges

C Chen, K Shu - arXiv preprint arXiv:2311.05656, 2023 - arxiv.org
Misinformation such as fake news and rumors is a serious threat on information ecosystems
and public trust. The emergence of Large Language Models (LLMs) has great potential to …

Large language model based multi-agents: A survey of progress and challenges

T Guo, X Chen, Y Wang, R Chang, S Pei… - arXiv preprint arXiv …, 2024 - arxiv.org
Large Language Models (LLMs) have achieved remarkable success across a wide array of
tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used …

Communicative agents for software development

C Qian, X Cong, C Yang, W Chen, Y Su, J Xu… - arXiv preprint arXiv …, 2023 - arxiv.org
Software engineering is a domain characterized by intricate decision-making processes,
often relying on nuanced intuition and consultation. Recent advancements in deep learning …

Exploring collaboration mechanisms for llm agents: A social psychology view

J Zhang, X Xu, S Deng - arXiv preprint arXiv:2310.02124, 2023 - arxiv.org
As Natural Language Processing (NLP) systems are increasingly employed in intricate
social environments, a pressing query emerges: Can these NLP systems mirror human …

How many unicorns are in this image? a safety evaluation benchmark for vision llms

H Tu, C Cui, Z Wang, Y Zhou, B Zhao, J Han… - arXiv preprint arXiv …, 2023 - arxiv.org
This work focuses on the potential of Vision LLMs (VLLMs) in visual reasoning. Different
from prior studies, we shift our focus from evaluating standard performance to introducing a …

Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents

Z Zhang, Y Yao, A Zhang, X Tang, X Ma, Z He… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have dramatically enhanced the field of language
intelligence, as demonstrably evidenced by their formidable empirical performance across a …

Editing personality for llms

S Mao, N Zhang, X Wang, M Wang, Y Yao… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper introduces an innovative task focused on editing the personality traits of Large
Language Models (LLMs). This task seeks to adjust the models' responses to opinion …

Mathdial: A dialogue tutoring dataset with rich pedagogical properties grounded in math reasoning problems

J Macina, N Daheim, SP Chowdhury, T Sinha… - arXiv preprint arXiv …, 2023 - arxiv.org
While automatic dialogue tutors hold great potential in making education personalized and
more accessible, research on such systems has been hampered by a lack of sufficiently …

Autoact: Automatic agent learning from scratch via self-planning

S Qiao, N Zhang, R Fang, Y Luo, W Zhou… - arXiv preprint arXiv …, 2024 - arxiv.org
Language agents have achieved considerable performance on various complex tasks.
Despite the incessant exploration in this field, existing language agent systems still struggle …

AI for social science and social science of AI: A survey

R Xu, Y Sun, M Ren, S Guo, R Pan, H Lin, L Sun… - Information Processing …, 2024 - Elsevier
Recent advancements in artificial intelligence, particularly with the emergence of large
language models (LLMs), have sparked a rethinking of artificial general intelligence …