"prompt tuning" Papers
47 papers found
Conference
Achieving More with Less: Additive Prompt Tuning for Rehearsal-Free Class-Incremental Learning
Haoran Chen, Ping Wang, Zihan Zhou et al.
CAPrompt: Cyclic Prompt Aggregation for Pre-Trained Model Based Class Incremental Learning
Qiwei Li, Jiahuan Zhou
Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning
Yilun Li, Miaomiao Cheng, Xu Han et al.
Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting
Wei Chen, Yuxuan Liang
FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models
Mainak Singha, Subhankar Roy, Sarthak Mehrotra et al.
FLOPS: Forward Learning with OPtimal Sampling
Tao Ren, Zishi Zhang, Jinyang Jiang et al.
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency
Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani et al.
LLM-enhanced Action-aware Multi-modal Prompt Tuning for Image-Text Matching
Meng Tian, Shuo Yang, Xinxiao Wu
MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning
Wenhao Gu, Li Gu, Ching Suen et al.
Multi-Domain Graph Foundation Models: Robust Knowledge Transfer via Topology Alignment
Shuo Wang, Bokui Wang, Zhixiang Shen et al.
Progressive Homeostatic and Plastic Prompt Tuning for Audio-Visual Multi-Task Incremental Learning
Jiong Yin, Liang Li, Jiehua Zhang et al.
Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer
Ningyuan Zhang, Jie Lu, Keqiuyin Li et al.
R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning
Lijun Sheng, Jian Liang, Zilei Wang et al.
SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only Passes
Yifan Yang, Zhen Zhang, Rupak Vignesh Swaminathan et al.
Skip Tuning: Pre-trained Vision-Language Models are Effective and Efficient Adapters Themselves
Shihan Wu, Ji Zhang, Pengpeng Zeng et al.
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model
Huan Ma, Yan Zhu, Changqing Zhang et al.
Understanding Prompt Tuning and In-Context Learning via Meta-Learning
Tim Genewein, Kevin Li, Jordi Grau-Moya et al.
Visual and Semantic Prompt Collaboration for Generalized Zero-Shot Learning
Huajie Jiang, Zhengxian Li, Xiaohan Yu et al.
Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models
Jie ZHANG, Xiaosong Ma, Song Guo et al.
AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models
Zhaopeng Gu, Bingke Zhu, Guibo Zhu et al.
Bottom-Up Domain Prompt Tuning for Generalized Face Anti-Spoofing
SI-QI LIU, Qirui Wang, Pong Chi Yuen
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
Jiahan Zhang, Qi Wei, Feng Liu et al.
Compound Text-Guided Prompt Tuning via Image-Adaptive Cues
Hao Tan, Jun Li, Yizhuang Zhou et al.
Controllable Prompt Tuning For Balancing Group Distributional Robustness
Hoang Phan, Andrew Wilson, Qi Lei
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.
DePT: Decoupled Prompt Tuning
Ji Zhang, Shihan Wu, Lianli Gao et al.
DGL: Dynamic Global-Local Prompt Tuning for Text-Video Retrieval
Xiangpeng Yang, Linchao Zhu, Xiaohan Wang et al.
DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning
Sikai Bai, Jie ZHANG, Song Guo et al.
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models
Jingwei Sun, Ziyue Xu, Hongxu Yin et al.
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning
Shangchao Su, Mingzhao Yang, Bin Li et al.
Harmonizing Generalization and Personalization in Federated Prompt Learning
Tianyu Cui, Hongxia Li, Jingya Wang et al.
Labels Need Prompts Too: Mask Matching for Natural Language Understanding Tasks
Bo Li, Wei Ye, Quansen Wang et al.
LAMM: Label Alignment for Multi-Modal Prompt Learning
Jingsheng Gao, Jiacheng Ruan, Suncheng Xiang et al.
MagicEraser: Erasing Any Objects via Semantics-Aware Control
FAN LI, Zixiao Zhang, Yi Huang et al.
One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models
Lin Li, Haoyan Guan, Jianing Qiu et al.
POET: Prompt Offset Tuning for Continual Human Action Adaptation
Prachi Garg, Joseph K J, Vineeth N Balasubramanian et al.
Prompt-based Visual Alignment for Zero-shot Policy Transfer
Haihan Gao, Rui Zhang, Qi Yi et al.
PromptFusion: Decoupling Stability and Plasticity for Continual Learning
Haoran Chen, Zuxuan Wu, Xintong Han et al.
Prompting a Pretrained Transformer Can Be a Universal Approximator
Aleksandar Petrov, Phil Torr, Adel Bibi
Prompting Language-Informed Distribution for Compositional Zero-Shot Learning
Wentao Bao, Lichang Chen, Heng Huang et al.
Prompt-tuning Latent Diffusion Models for Inverse Problems
Hyungjin Chung, Jong Chul YE, Peyman Milanfar et al.
ProS: Prompting-to-simulate Generalized knowledge for Universal Cross-Domain Retrieval
Fang Kaipeng, Jingkuan Song, Lianli Gao et al.
Quantized Prompt for Efficient Generalization of Vision-Language Models
Tianxiang Hao, Xiaohan Ding, Juexiao Feng et al.
SDPT: Synchronous Dual Prompt Tuning for Fusion-based Visual-Language Pre-trained Models
Yang Zhou, Yongjian Wu, Jiya Saiyin et al.
Test-Time Personalization with Meta Prompt for Gaze Estimation
Huan Liu, Julia Qi, Zhenhao Li et al.
Two-stage LLM Fine-tuning with Less Specialization and More Generalization
Yihan Wang, Si Si, Daliang Li et al.
Weak Distribution Detectors Lead to Stronger Generalizability of Vision-Language Prompt Tuning
Kun Ding, Haojian Zhang, Qiang Yu et al.