QG-MIL: A Gated Transformer Aggregator for Domain-Agnostic Multiple Instance Learning in Medical Imaging
QG-MIL introduces a gated transformer aggregator for multiple instance learning in medical imaging that stabilizes attention distribution and improves prediction consistency across…
Hugging Face · Daily Papers
·Luca Zedda, Davide Antonio Mura
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·▲ 2 upvotes
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Autores: Luca Zedda, Davide Antonio Mura, Cecilia Di Ruberto, Maurizio Atzori, Muhammed Furkan Dasdelen, Carsten Marr
- 2 upvotes da comunidade
- Temas: Attention-based Multiple Instance Learning, gated transformer aggregator, RMSNorm-based pre-normalization, per-head QK normalization, fine-grained attention output gating, SwiGLU-style feed-forward modules
Resumo
Resumo original (em inglês), extraído do paper:
QG-MIL introduces a gated transformer aggregator for multiple instance learning in medical imaging that stabilizes attention distribution and improves prediction consistency across different medical domains.