PR-MaGIC: Prompt Refinement Via Mask Decoder Gradient Flow For In-Context Segmentation

arXiv:2604.12113 · cs.CV, cs.AI · Submitted 2026-04-13 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-04-13

Updated: 2026-10-13

Project page: https://postech-minjaelee.github.io/PR-MaGIC/Abstract

Terminology

• Gradient Flow — 3× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Segment Anything Model — 1× in this paper
• Segment Anything Model (SAM) — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes

Sources

• One-Shot Learning for Semantic Segmentation
• LLaMA: Open and Efficient Foundation Language Models
• Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
• GLM-130B: An Open Bilingual Pre-trained Model
• Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

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