Guided Prompt Evolution for Vision-Language Models Adaptation

arXiv:2603.09493 · cs.CV, cs.AI · Submitted 2026-03-10 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-03-10

Updated: 2026-09-01

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Adaptation — 28× in this paper · explained in 1 episode
• Generalization — 22× in this paper · explained in 13 episodes
• Few-Shot Learning — 7× in this paper · explained in 4 episodes
• Regularization — 7× in this paper · explained in 3 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Alignment — 6× in this paper · explained in 1 episode
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Core — 5× in this paper · explained in 2 episodes
• Modality-Shared Prompt Projector — 5× in this paper
• Transformer — 5× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 4× in this paper · explained in 5 episodes
• Downstream Tasks — 4× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 4× in this paper · explained in 6 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Feature Geometric Regularization — 3× in this paper
• Foundation Model — 3× in this paper · explained in 3 episodes
• Representation Learning — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Transfer Learning — 3× in this paper · explained in 10 episodes
• Zero-Shot Generalization — 3× in this paper · explained in 5 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Decoupling — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Optimal Transport — 2× in this paper · explained in 5 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Adversarial Examples — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Continual Learning — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Frozen model — 1× in this paper · explained in 3 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Parameter-Efficient Fine-Tuning — 1× in this paper · explained in 2 episodes
• Parameter-Efficient Fine-Tuning (PEFT) — 1× in this paper · explained in 4 episodes
• Predictive Coding — 1× in this paper · explained in 2 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Fine-Grained Visual Classification of Aircraft
• Representation Learning with Contrastive Predictive Coding
• UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
• SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning
• Efficient Construction of Model Family through Progressive Training Using Model Expansion

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