3 citations · 5 across the 13 of their papers we have counts for
6 papers · 1 filter
Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration
Mingtao Xian, Yifeng Yang, Qinying Gu +2
Multimodal Large Language Models (MLLMs) have shown strong performance in multi-image cross-modal retrieval, yet suffer from severe position bias, where predictions are dominated b…
TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection
Yifeng Yang, Jubo Feng, Jing Xu +3
Vision-language models enable OOD detection by comparing image alignment with ID labels and negative semantics. Existing negative-label-based methods mainly rely on static negative…
: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization
Lin Zhu, Yifeng Yang, Xinbing Wang +2
Recent approaches for vision-language models (VLMs) have shown remarkable success in achieving fast downstream adaptation. When applied to real-world downstream tasks, VLMs inevita…
OODD: Test-time Out-of-Distribution Detection with Dynamic Dictionary
Yifeng Yang, Lin Zhu, Zewen Sun +3
Out-of-distribution (OOD) detection remains challenging for deep learning models, particularly when test-time OOD samples differ significantly from training outliers. We propose OO…
Visual Position Prompt for MLLM based Visual Grounding
Wei Tang, Yanpeng Sun, Qinying Gu +1
Although Multimodal Large Language Models (MLLMs) excel at various image-related tasks, they encounter challenges in precisely aligning coordinates with spatial information within…
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection
Lin Zhu, Yifeng Yang, Qinying Gu +3
Recent vision-language pre-trained models (VL-PTMs) have shown remarkable success in open-vocabulary tasks. However, downstream use cases often involve further fine-tuning of VL-PT…