Performance Analysis
Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space
A new framework is proposed in this paper to address these issues.
Kernel PCA for Out-of-Distribution Detection Kun Fang
Out-of-Distribution (OoD) detection is vital for the reliability of Deep Neural Networks (DNNs).
ChronoEpilogi: Scalable Time-Series Variable Selection with Multiple Solutions
Lasso performance, with the added benefit of providing multiple solutions.
CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models Junho Kim Hyun Jun Kim Y eon Ju Kim Yong Man Ro
Large Multi-modal Models (LMMs) have recently demonstrated remarkable abilities in visual context understanding and coherent response generation.
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection Xinting Liao
FL further makes efforts to adapt real-world scenarios, i.e., adapting
The iNaturalist Sounds Dataset
A current gap in the acoustic space is a large-scale, fine-grained dataset of species sounds that is easy to download and easy to use.