Visual Prompt Tuning

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 37 papers with code (70 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Visual Prompt Tuning
  23 Mar 2022 6 repositories listed Syntology ran 17 of 27 samples · 10 unverified · 15 pointer-only (licence)
  The current modus operandi in adapting pre-trained models involves updating all the backbone parameters, ie, full fine-tuning.
• Improving Visual Prompt Tuning by Gaussian Neighborhood Minimization for Long-Tailed Visual Recognition
  28 Oct 2024 3 repositories listed Syntology ran 1 of 8 samples · 7 unverified
  To address this issue, we propose a novel method called Random SAM prompt tuning (RSAM-PT) to improve the model generalization, requiring only one-step gradient computation at each step.
• Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models
  14 Apr 2023 3 repositories listed Syntology ran 9 of 14 samples · 5 unverified · 14 pointer-only (licence)
  To conquer this limitation, we propose a novel Instance-aware Dynamic Prompt Tuning (IDPT) strategy for pre-trained point cloud models.
• Understanding Zero-Shot Adversarial Robustness for Large-Scale Models
  14 Dec 2022 2 repositories listed
  We apply this training loss to two adaption methods, model finetuning and visual prompt tuning.
• Attention to Burstiness: Low-Rank Bilinear Prompt Tuning
  28 Jun 2025 1 repository listed
  Visual Prompt Tuning (VPT) is a parameter-efficient fune-tuning technique that adapts a pre-trained vision Transformer (ViT) by learning a small set of parameters in the input space, known as prompts.
• DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformers
  29 May 2025 1 repository listed Syntology ran 4 of 5 samples · 1 unverified
  The results demonstrate that our approach enables more effective and efficient fine-tuning of ViT models by leveraging semantic information to guide the learning of the prompts, leading to improved performance on…
• Q-Adapt: Adapting LMM for Visual Quality Assessment with Progressive Instruction Tuning
  2 Apr 2025 1 repository listed
  To mitigate this, we propose a new paradigm for perception-oriented instruction tuning, i.
• Iterative Prompt Relocation for Distribution-Adaptive Visual Prompt Tuning
  10 Mar 2025 1 repository listed
  Specifically, we develop a prompt relocation strategy for ADO derived from this formulation, comprising two optimization steps: identifying and pruning idle prompts, followed by determining the optimal blocks for their…
• Prompt-CAM: A Simpler Interpretable Transformer for Fine-Grained Analysis
  16 Jan 2025 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  We present a simple usage of pre-trained Vision Transformers (ViTs) for fine-grained analysis, aiming to identify and localize the traits that distinguish visually similar categories, such as different bird species or…
• Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis
  1 Jan 2025 1 repository listed
  We present a simple approach to make pre-trained Vision Transformers (ViTs) interpretable for fine-grained analysis, aiming to identify and localize the traits that distinguish visually similar categories, such as bird…
• Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning
  22 Dec 2024 1 repository listed
  We adaptively construct semantic hierarchies and use semantic-independent and semantic-shared prompts to learn hierarchical representations.
• Med-PerSAM: One-Shot Visual Prompt Tuning for Personalized Segment Anything Model in Medical Domain
  25 Nov 2024 1 repository listed
  To address these challenges, we introduce \textbf{Med-PerSAM}, a novel and straightforward one-shot framework designed for the medical domain.
• Visual Fourier Prompt Tuning
  2 Nov 2024 1 repository listed Syntology ran 3 of 17 samples · 14 unverified · 17 pointer-only (licence)
  To address this challenge, we draw inspiration from human visual cognition, and propose the Visual Fourier Prompt Tuning (VFPT) method as a general and effective solution for adapting large-scale transformer-based…
• TuneVLSeg: Prompt Tuning Benchmark for Vision-Language Segmentation Models
  7 Oct 2024 1 repository listed
  This work presents an open-source benchmarking framework, TuneVLSeg, to integrate various unimodal and multimodal prompt tuning techniques into VLSMs, making prompt tuning usable for downstream segmentation datasets…
• CVPT: Cross-Attention help Visual Prompt Tuning adapt visual task
  27 Aug 2024 1 repository listed Syntology ran 5 of 6 samples · 1 unverified · 6 pointer-only (licence)
  These methods optimize large-scale pre-trained models for specific tasks by fine-tuning a select group of parameters.
• SAN: Hypothesizing Long-Term Synaptic Development and Neural Engram Mechanism in Scalable Model's Parameter-Efficient Fine-Tuning
  24 Aug 2024 1 repository listed Syntology ran 7 of 10 samples · 3 unverified · 10 pointer-only (licence)
  Advances in Parameter-Efficient Fine-Tuning (PEFT) bridged the performance gap with Full Fine-Tuning (FFT) through sophisticated analysis of pre-trained parameter spaces.
• Visual Prompt Tuning in Null Space for Continual Learning
  9 Jun 2024 1 repository listed Syntology ran 12 of 19 samples · 7 unverified
  Existing prompt-tuning methods have demonstrated impressive performances in continual learning (CL), by selecting and updating relevant prompts in the vision-transformer models.
• TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt
  11 May 2024 1 repository listed Syntology ran 8 of 10 samples · 2 unverified · 10 pointer-only (licence)
  Then, a co-learning strategy with a dual-adapter module is designed to transfer visual knowledge from pseudo-visual prompt to text prompt, enhancing their visual representation abilities.
• ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt Tuning
  29 Mar 2024 1 repository listed Syntology ran 3 of 4 samples · 1 unverified · 4 pointer-only (licence)
  Panoptic segmentation, combining semantic and instance segmentation, stands as a cutting-edge computer vision task.
• CoDA: Instructive Chain-of-Domain Adaptation with Severity-Aware Visual Prompt Tuning
  26 Mar 2024 1 repository listed
  SAVPT features a novel metric Severity that divides all adverse scene images into low-severity and high-severity images.
• CoLLaVO: Crayon Large Language and Vision mOdel
  17 Feb 2024 1 repository listed Syntology ran 5 of 6 samples · 1 unverified
  Our findings reveal that the image understanding capabilities of current VLMs are strongly correlated with their zero-shot performance on vision language (VL) tasks.
• Facing the Elephant in the Room: Visual Prompt Tuning or Full Finetuning?
  23 Jan 2024 1 repository listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)
  As the scale of vision models continues to grow, the emergence of Visual Prompt Tuning (VPT) as a parameter-efficient transfer learning technique has gained attention due to its superior performance compared to…
• SA²VP: Spatially Aligned-and-Adapted Visual Prompt
  16 Dec 2023 1 repository listed Syntology ran 10 of 14 samples · 4 unverified · 4 pointer-only (licence)
  Typical methods for visual prompt tuning follow the sequential modeling paradigm stemming from NLP, which represents an input image as a flattened sequence of token embeddings and then learns a set of unordered…
• TSP-Transformer: Task-Specific Prompts Boosted Transformer for Holistic Scene Understanding
  6 Nov 2023 1 repository listed
  Holistic scene understanding includes semantic segmentation, surface normal estimation, object boundary detection, depth estimation, etc.
• Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning
  27 Oct 2023 1 repository listed Syntology ran 7 of 14 samples · 7 unverified
  Existing Generalized FL (GFL) and Personalized FL (PFL) methods have limitations in balancing performance across both global and local data distributions.
• From Question to Exploration: Test-Time Adaptation in Semantic Segmentation?
  9 Oct 2023 1 repository listed
  Second, although the teacher-student scheme does enhance the training stability for segmentation TTA in the presence of noisy pseudo-labels and temporal correlation, it cannot directly result in performance improvement…
• Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning
  18 Aug 2023 1 repository listed
  In addition, to alleviate the class imbalance problem, we introduce a new gradient similarity-based focal loss and adaptive feature scaling to ease overfitting to the major classes and underfitting to the minor classes.
• E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
  25 Jul 2023 1 repository listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)
  Specifically, we introduce a set of learnable key-value prompts and visual prompts into self-attention and input layers, respectively, to improve the effectiveness of model fine-tuning.
• DVPT: Dynamic Visual Prompt Tuning of Large Pre-trained Models for Medical Image Analysis
  19 Jul 2023 1 repository listed
  Firstly, the frozen features are transformed by an lightweight bottleneck layer to learn the domain-specific distribution of downstream medical tasks, and then a few learnable visual prompts are used as dynamic queries…
• Uncertainty-aware State Space Transformer for Egocentric 3D Hand Trajectory Forecasting
  17 Jul 2023 1 repository listed Syntology ran 9 of 13 samples · 4 unverified
  In this paper, we set up an egocentric 3D hand trajectory forecasting task that aims to predict hand trajectories in a 3D space from early observed RGB videos in a first-person view.

Syntology lines on 17 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.