| Causality-guided Prompt Learning for Vision-language Models via Visual Granulation | | 77.80 | CaPL | 2025-09-04 |
| MERGETUNE: Continued Fine-Tuning of Vision-Language Models | ✓ Link | 77.77 | PromptKD + MergeTune | 2026-01-15 |
| PromptKD: Unsupervised Prompt Distillation for Vision-Language Models | ✓ Link | 77.62 | PromptKD | 2024-03-05 |
| Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models | ✓ Link | 75.49 | Customized Ensemble | 2023-11-28 |
| GLAD: Generalizable Tuning for Vision-Language Models | | 75.04 | GLAD | 2025-07-17 |
| DeAR: Fine-Grained VLM Adaptation by Decomposing Attention Head Roles | ✓ Link | 74.83 | DeAR | 2026-03-01 |
| SpecPL: Disentangling Spectral Granularity for Prompt Learning | ✓ Link | 74.63 | MMRL + SpecPL | 2026-05-06 |
| Fourier-Attentive Representation Learning: A Fourier-Guided Framework for Few-Shot Generalization in Vision-Language Models | | 74.53 | FARL | 2025-12-04 |
| RMAdapter: Reconstruction-based Multi-Modal Adapter for Vision-Language Models | | 74.52 | RMAdapter | 2025-12-07 |
| MMRL: Multi-Modal Representation Learning for Vision-Language Models | ✓ Link | 74.45 | MMRL | 2025-03-11 |
| MMRL++: Parameter-Efficient and Interaction-Aware Representation Learning for Vision-Language Models | ✓ Link | 74.44 | MMRL++ | 2025-05-15 |
| HeBA: Heterogeneous Bottleneck Adapters for Robust Vision-Language Models | ✓ Link | 74.41 | HeBA | 2026-03-17 |
| Robust Prompt Tuning for Vision-Language Models with Mild Semantic Noise | | 74.35 | ANPrompt | 2025-08-06 |
| Consistency-guided Prompt Learning for Vision-Language Models | ✓ Link | 74.33 | CoPrompt | 2023-06-01 |
| HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling | ✓ Link | 74.24 | HPT++ | 2024-08-27 |
| Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models | ✓ Link | 74.17 | HPT | 2023-12-11 |
| AttriPrompt: Dynamic Prompt Composition Learning for CLIP | | 74.17 | AttriPrompt | 2025-09-07 |
| Prompt Learning via Meta-Regularization | ✓ Link | 74.09 | ProMetaR | 2024-04-01 |
| Learning Domain Invariant Prompt for Vision-Language Models | ✓ Link | 74.02 | MetaPrompt | 2022-12-08 |
| DePT: Decoupled Prompt Tuning | ✓ Link | 74.02 | DePT | 2023-09-14 |
| Self-regulating Prompts: Foundational Model Adaptation without Forgetting | ✓ Link | 74.01 | PromptSRC | 2023-07-13 |
| Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning | | 74.01 | PromptSRC + IPL | 2026-05-06 |
| Read-only Prompt Optimization for Vision-Language Few-shot Learning | ✓ Link | 74.00 | RPO | 2023-08-29 |
| MERGETUNE: Continued Fine-Tuning of Vision-Language Models | ✓ Link | 74.00 | MMA + MergeTune | 2026-01-15 |
| One Last Attention for Your Vision-Language Model | ✓ Link | 73.89 | RAda + Adapter | 2025-07-21 |
| Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning | | 73.48 | MaPLe + IPL | 2026-05-06 |
| ProCAP: Probabilistic Cross-Attentive Prompt Learning for Vision-Language Models | ✓ Link | 73.48 | ProCAP | 2026-09-24 |
| MaPLe: Multi-modal Prompt Learning | ✓ Link | 73.47 | MaPLe | 2022-10-06 |
| Gram-Anchored Prompt Learning for Vision-Language Models via Second-Order Statistics | | 73.40 | GAPL | 2026-04-05 |
| SpecPL: Disentangling Spectral Granularity for Prompt Learning | ✓ Link | 73.34 | CoOp + SpecPL | 2026-05-06 |
| Conditional Prompt Learning for Vision-Language Models | ✓ Link | 73.10 | CoCoOp | 2022-03-10 |
| Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning | | 73.10 | CoCoOp + IPL | 2026-05-06 |
| Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning | | 73.02 | KgCoOp + IPL | 2026-05-06 |
| SpecPL: Disentangling Spectral Granularity for Prompt Learning | ✓ Link | 72.97 | MaPLe + SpecPL | 2026-05-06 |
| MERGETUNE: Continued Fine-Tuning of Vision-Language Models | ✓ Link | 72.81 | CoOp + MergeTune | 2026-01-15 |
| MERGETUNE: Continued Fine-Tuning of Vision-Language Models | ✓ Link | 72.75 | KgCoOp + MergeTune | 2026-01-15 |
| SpecPL: Disentangling Spectral Granularity for Prompt Learning | ✓ Link | 72.52 | CoCoOp + SpecPL | 2026-05-06 |
| One Last Attention for Your Vision-Language Model | ✓ Link | 72.44 | RAda + Prompt | 2025-07-21 |
| One Last Attention for Your Vision-Language Model | ✓ Link | 71.78 | RAda | 2025-07-21 |
| Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning | | 70.85 | CoOp + IPL | 2026-05-06 |
| Learning Transferable Visual Models From Natural Language Supervision | ✓ Link | 70.22 | CLIP | 2021-02-26 |