Artificial intelligence for science in quantum, atomistic, and continuum systems

X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie… - arXiv preprint arXiv …, 2023 - arxiv.org
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Hallucination of multimodal large language models: A survey

Z Bai, P Wang, T Xiao, T He, Z Han, Z Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
This survey presents a comprehensive analysis of the phenomenon of hallucination in
multimodal large language models (MLLMs), also known as Large Vision-Language Models …

Halle-switch: Rethinking and controlling object existence hallucinations in large vision language models for detailed caption

B Zhai, S Yang, X Zhao, C Xu, S Shen, D Zhao… - arXiv preprint arXiv …, 2023 - arxiv.org
Current large vision-language models (LVLMs) achieve remarkable progress, yet there
remains significant uncertainty regarding their ability to accurately apprehend visual details …

Decoding the silent majority: Inducing belief augmented social graph with large language model for response forecasting

C Sun, J Li, YR Fung, HP Chan, T Abdelzaher… - arXiv preprint arXiv …, 2023 - arxiv.org
Automatic response forecasting for news media plays a crucial role in enabling content
producers to efficiently predict the impact of news releases and prevent unexpected …

Normsage: Multi-lingual multi-cultural norm discovery from conversations on-the-fly

YR Fung, T Chakraborty, H Guo, O Rambow… - arXiv preprint arXiv …, 2022 - arxiv.org
Norm discovery is important for understanding and reasoning about the acceptable
behaviors and potential violations in human communication and interactions. We introduce …

Fake artificial intelligence generated contents (FAIGC): a survey of theories, detection methods, and opportunities

X Yu, Y Wang, Y Chen, Z Tao, D Xi, S Song… - arXiv preprint arXiv …, 2024 - arxiv.org
In recent years, generative artificial intelligence models, represented by Large Language
Models (LLMs) and Diffusion Models (DMs), have revolutionized content production …

Defining a new NLP playground

S Li, C Han, P Yu, C Edwards, M Li, X Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
The recent explosion of performance of large language models (LLMs) has changed the
field of Natural Language Processing (NLP) more abruptly and seismically than any other …

Persona-db: Efficient large language model personalization for response prediction with collaborative data refinement

C Sun, K Yang, RG Reddy, YR Fung, HP Chan… - arXiv preprint arXiv …, 2024 - arxiv.org
The increasing demand for personalized interactions with large language models (LLMs)
calls for methodologies capable of accurately and efficiently identifying user opinions and …

Autoprm: Automating procedural supervision for multi-step reasoning via controllable question decomposition

Z Chen, Z Zhao, Z Zhu, R Zhang, X Li, B Raj… - arXiv preprint arXiv …, 2024 - arxiv.org
Recent advancements in large language models (LLMs) have shown promise in multi-step
reasoning tasks, yet their reliance on extensive manual labeling to provide procedural …

Language+ Molecules

C Edwards, Q Wang, H Ji - Proceedings of the 18th Conference of …, 2024 - aclanthology.org
Climate change, access to food and water, pandemics–the world faces an enormous
number of problems in the coming decades on scales of complexity never-before-seen. To …