JMMMU: A Japanese Massive Multi-discipline Multimodal Understanding Benchmark for Culture-aware Evaluation Paper • 2410.17250 • Published Oct 22, 2024 • 15
JMMMU: A Japanese Massive Multi-discipline Multimodal Understanding Benchmark for Culture-aware Evaluation Paper • 2410.17250 • Published Oct 22, 2024 • 15
JMMMU: A Japanese Massive Multi-discipline Multimodal Understanding Benchmark for Culture-aware Evaluation Paper • 2410.17250 • Published Oct 22, 2024 • 15
Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey Paper • 2407.21794 • Published Jul 31, 2024 • 6
Unsolvable Problem Detection: Evaluating Trustworthiness of Vision Language Models Paper • 2403.20331 • Published Mar 29, 2024 • 16
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning Paper • 2306.01293 • Published Jun 2, 2023
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation Paper • 2210.12681 • Published Oct 23, 2022
Zero-Shot In-Distribution Detection in Multi-Object Settings Using Vision-Language Foundation Models Paper • 2304.04521 • Published Apr 10, 2023
Can Pre-trained Networks Detect Familiar Out-of-Distribution Data? Paper • 2310.00847 • Published Oct 2, 2023