Classic fault detection and classification has some classic problems. It’s reactive, time-consuming to set up, and any ...

We present Multi-SpatialMLLM to equip MLLMs with robust multi-frame spatial understanding by integrating depth perception, visual correspondence, and dynamic perception.

Discriminative least squares regression (DLSR) is a simple yet effective method for multi-class classification. One problem of DLSR is that it is lack of robustness to outliers. In order to tackle ...

Source code of our paper "Multi-Agent Consensus Seeking via Large Language Models". - WindyLab/ConsensusLLM-code ...

An effective way to solve multi-class classification problems is the One-Versus-One (OVO) decomposition strategy. When applying the OVO strategy to practice, there may be a `tie vote' phenomenon so ...