4 papers
EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation
Shu-Hao Zhang, Le-Tong Huang, Xiang-Sheng Deng +5
Quantization has emerged as a mainstream approach for deploying Large Language Models (LLMs) on resource-constrained devices, yet compressing precision below 4-bit typically causes…
Theoretical Investigation on Inductive Bias of Isolation Forest
Qin-Cheng Zheng, Shao-Qun Zhang, Shen-Huan Lyu +2
Isolation Forest (iForest) stands out as a widely-used unsupervised anomaly detector, primarily owing to its remarkable runtime efficiency and superior performance in large-scale t…
Curriculum Abductive Learning
Wen-Chao Hu, Qi-Jie Li, Lin-Han Jia +4
Abductive Learning (ABL) integrates machine learning with logical reasoning in a loop: a learning model predicts symbolic concept labels from raw inputs, which are revised through…
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…