82 citations · 128 across the 8 of their papers we have counts for
4 papers · 1 filter
Neuro-symbolic Learning Yielding Logical Constraints
Zenan Li, Yunpeng Huang, Zhaoyu Li +5
Neuro-symbolic systems combine the abilities of neural perception and logical reasoning. However, end-to-end learning of neuro-symbolic systems is still an unsolved challenge. This…
Learning with Logical Constraints but without Shortcut Satisfaction
Zenan Li, Zehua Liu, Yuan Yao +4
Recent studies in neuro-symbolic learning have explored the integration of logical knowledge into deep learning via encoding logical constraints as an additional loss function. How…
Softened Symbol Grounding for Neuro-symbolic Systems
Zenan Li, Yuan Yao, Taolue Chen +4
Neuro-symbolic learning generally consists of two separated worlds, i.e., neural network training and symbolic constraint solving, whose success hinges on symbol grounding, a funda…
Securing Reliability: A Brief Overview on Enhancing In-Context Learning for Foundation Models
Yunpeng Huang, Yaonan Gu, Jingwei Xu +3
As foundation models (FMs) continue to shape the landscape of AI, the in-context learning (ICL) paradigm thrives but also encounters issues such as toxicity, hallucination, dispari…