4 papers
Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey
Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang +10
Detecting out-of-distribution (OOD) samples is crucial for ensuring the safety of machine learning systems and has shaped the field of OOD detection. Meanwhile, several other probl…
Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds
Yang Guo, Yutian Tao, Yifei Ming +2
Retrieval-augmented generation (RAG) has seen many empirical successes in recent years by aiding the LLM with external knowledge. However, its theoretical aspect has remained mostl…
Unsolvable Problem Detection: Robust Understanding Evaluation for Large Multimodal Models
Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang +7
This paper introduces a novel task to evaluate the robust understanding capability of Large Multimodal Models (LMMs), termed . Multiple…
HYPO: Hyperspherical Out-of-Distribution Generalization
Haoyue Bai, Yifei Ming, Julian Katz-Samuels +1
Out-of-distribution (OOD) generalization is critical for machine learning models deployed in the real world. However, achieving this can be fundamentally challenging, as it require…