XFlow: A Workflow Model for Instruction-Guided Lesion Segmentation in Chest X-rays

arXiv:2609.34513 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Terminology

• Benchmark — 7× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 4× in this paper
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• GRPO — 3× in this paper · explained in 6 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Bradley-Terry model — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Pseudo-labeling — 1× in this paper · explained in 3 episodes
• Quantifying Uncertainty — 1× in this paper · explained in 5 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Segment Anything Model — 1× in this paper
• Segment Anything Model (SAM) — 1× in this paper · explained in 2 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Vision-Language Model (VLM) — 1× in this paper · explained in 3 episodes

Sources

• CheXpercept: A Benchmark for Evaluating Expert-Level Lesion Perception in Chest X-rays
• CheXmask-U: Quantifying uncertainty in landmark-based anatomical segmentation for X-ray images
• LoRA: Low-Rank Adaptation of Large Language Models
• IBISAgent: Reinforcing Pixel-Level Visual Reasoning in MLLMs for Universal Biomedical Object Referring and Segmentation
• Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement
• MedSAM2: Segment Anything in 3D Medical Images and Videos
• Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling
• MedGemma 1.5 Technical Report
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Chest ImaGenome Dataset for Clinical Reasoning
• BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once

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