OpenCodePapers

prompt-engineering-on-oxford-iiit-pet-dataset

Transfer LearningPrompt Engineering
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PaperCodeHarmonic meanModelNameReleaseDate
Causality-guided Prompt Learning for Vision-language Models via Visual Granulation98.03CaPL2025-09-04
MERGETUNE: Continued Fine-Tuning of Vision-Language Models✓ Link97.48PromptKD + MergeTune2026-01-15
ProCAP: Probabilistic Cross-Attentive Prompt Learning for Vision-Language Models✓ Link97.34ProCAP2026-09-24
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models✓ Link97.15PromptKD2024-03-05
AttriPrompt: Dynamic Prompt Composition Learning for CLIP97.09AttriPrompt2025-09-07
One Last Attention for Your Vision-Language Model✓ Link97.01RAda + Prompt2025-07-21
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling✓ Link96.91HPT++2024-08-27
MERGETUNE: Continued Fine-Tuning of Vision-Language Models✓ Link96.91MMA + MergeTune2026-01-15
RMAdapter: Reconstruction-based Multi-Modal Adapter for Vision-Language Models96.89RMAdapter2025-12-07
Consistency-guided Prompt Learning for Vision-Language Models✓ Link96.87CoPrompt2023-06-01
Fourier-Attentive Representation Learning: A Fourier-Guided Framework for Few-Shot Generalization in Vision-Language Models96.86FARL2025-12-04
DeAR: Fine-Grained VLM Adaptation by Decomposing Attention Head Roles✓ Link96.81DeAR2026-03-01
SpecPL: Disentangling Spectral Granularity for Prompt Learning✓ Link96.81MaPLe + SpecPL2026-05-06
Gram-Anchored Prompt Learning for Vision-Language Models via Second-Order Statistics96.80GAPL2026-04-05
SpecPL: Disentangling Spectral Granularity for Prompt Learning✓ Link96.80MMRL + SpecPL2026-05-06
GLAD: Generalizable Tuning for Vision-Language Models96.78GLAD2025-07-17
MMRL: Multi-Modal Representation Learning for Vision-Language Models✓ Link96.74MMRL2025-03-11
Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning96.72PromptSRC + IPL2026-05-06
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models✓ Link96.71HPT2023-12-11
One Last Attention for Your Vision-Language Model✓ Link96.69RAda + Adapter2025-07-21
Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning96.62MaPLe + IPL2026-05-06
Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning96.61CoCoOp + IPL2026-05-06
MaPLe: Multi-modal Prompt Learning✓ Link96.58MaPLe2022-10-06
MERGETUNE: Continued Fine-Tuning of Vision-Language Models✓ Link96.53KgCoOp + MergeTune2026-01-15
MMRL++: Parameter-Efficient and Interaction-Aware Representation Learning for Vision-Language Models✓ Link96.51MMRL++2025-05-15
Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning96.51KgCoOp + IPL2026-05-06
Prompt Learning via Meta-Regularization✓ Link96.49ProMetaR2024-04-01
SpecPL: Disentangling Spectral Granularity for Prompt Learning✓ Link96.45CoCoOp + SpecPL2026-05-06
Robust Prompt Tuning for Vision-Language Models with Mild Semantic Noise96.44ANPrompt2025-08-06
Conditional Prompt Learning for Vision-Language Models✓ Link96.43CoCoOp2022-03-10
MERGETUNE: Continued Fine-Tuning of Vision-Language Models✓ Link96.40CoOp + MergeTune2026-01-15
DePT: Decoupled Prompt Tuning✓ Link96.37DePT2023-09-14
HeBA: Heterogeneous Bottleneck Adapters for Robust Vision-Language Models✓ Link96.35HeBA2026-03-17
Self-regulating Prompts: Foundational Model Adaptation without Forgetting✓ Link96.30PromptSRC2023-07-13
Learning Domain Invariant Prompt for Vision-Language Models✓ Link96.26MetaPrompt2022-12-08
Read-only Prompt Optimization for Vision-Language Few-shot Learning✓ Link96.05RPO2023-08-29
Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning95.99CoOp + IPL2026-05-06
SpecPL: Disentangling Spectral Granularity for Prompt Learning✓ Link95.79CoOp + SpecPL2026-05-06
One Last Attention for Your Vision-Language Model✓ Link95.16RAda2025-07-21
Learning Transferable Visual Models From Natural Language Supervision✓ Link94.12CLIP2021-02-26
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