6 papers · 1 filter
Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models
Xiao-Wen Yang, Jie-Jing Shao, Lan-Zhe Guo +5
Large Language Models (LLMs) have shown promising results across various tasks, yet their reasoning capabilities remain a fundamental challenge. Developing AI systems with strong r…
Efficient Rectification of Neuro-Symbolic Reasoning Inconsistencies by Abductive Reflection
Wen-Chao Hu, Wang-Zhou Dai, Yuan Jiang +1
Neuro-Symbolic (NeSy) AI could be regarded as an analogy to human dual-process cognition, modeling the intuitive System 1 with neural networks and the algorithmic System 2 with sym…
Human Comprehensible Active Learning of Genome-Scale Metabolic Networks
Lun Ai, Shi-Shun Liang, Wang-Zhou Dai +3
An important application of Synthetic Biology is the engineering of the host cell system to yield useful products. However, an increase in the scale of the host system leads to hug…
Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees
Lue Tao, Yu-Xuan Huang, Wang-Zhou Dai +1
Neuro-symbolic hybrid systems are promising for integrating machine learning and symbolic reasoning, where perception models are facilitated with information inferred from a symbol…
Automated Biodesign Engineering by Abductive Meta-Interpretive Learning
Wang-Zhou Dai, Liam Hallett, Stephen H. Muggleton +1
The application of Artificial Intelligence (AI) to synthetic biology will provide the foundation for the creation of a high throughput automated platform for genetic design, in whi…
Tunneling Neural Perception and Logic Reasoning through Abductive Learning
Wang-Zhou Dai, Qiu-Ling Xu, Yang Yu +1
Perception and reasoning are basic human abilities that are seamlessly connected as part of human intelligence. However, in current machine learning systems, the perception and rea…