LAGO: Language-Guided Adaptive Object-Region Focus for Zero-Shot Visual-Text Alignment

arXiv:2605.08156 · cs.CV, cs.AI · Submitted 2026-05-04 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-05-04

Updated: 2026-09-26

Terminology

• Alignment — 64× in this paper · explained in 1 episode
• Aggregation — 23× in this paper · explained in 1 episode
• Distribution Shift — 20× in this paper · explained in 6 episodes
• Accuracy — 12× in this paper · explained in 1 episode
• Ablation — 10× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• Robustness — 8× in this paper · explained in 5 episodes
• Redundancy — 7× in this paper · explained in 2 episodes
• Grounding — 6× in this paper · explained in 3 episodes
• Alignment Methods — 5× in this paper · explained in 1 episode
• Calibration — 5× in this paper · explained in 7 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Zero-Shot Generalization — 3× in this paper · explained in 5 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Adaptive Strategy — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Semi-supervised Learning — 2× in this paper · explained in 4 episodes
• Visual Grounding — 2× in this paper · explained in 2 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Alignment Problem — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Pseudo-labeling — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Two-Stage Framework — 1× in this paper · explained in 2 episodes

Sources

• FG-CLIP: Fine-Grained Visual and Textual Alignment
• Unified Vision and Language Prompt Learning
• MaPLe: Multi-modal Prompt Learning
• Learning to Prompt with Text Only Supervision for Vision-Language Models
• Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
• Toward Visual Grounding: A Survey
• Image-of-Thought Prompting for Visual Reasoning Refinement in Multimodal Large Language Models
• Adaptive Chain-of-Focus Reasoning via Dynamic Visual Search and Zooming for Efficient VLMs
• VGR: Visual Grounded Reasoning
• Fast Segment Anything

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