https://github.com/munish30monga/COSMo
공식 코드COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation
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COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
Enhancing Biomedical Relation Extraction with Directionality
PromptSmooth: Certifying Robustness of Medical Vision-Language Models via Prompt Learning
Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation
Say More with Less: Understanding Prompt Learning Behaviors through Gist Compression
Forensics Adapter: Unleashing CLIP for Generalizable Face Forgery Detection
$\textbf{S}^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zero-Shot Rumor Detection with Propagation Structure via Prompt Learning
Zero-shot Generative Model Adaptation via Image-specific Prompt Learning
Lifelong Knowledge Editing for LLMs with Retrieval-Augmented Continuous Prompt Learning
NLPrompt: Noise-Label Prompt Learning for Vision-Language Models
LW2G: Learning Whether to Grow for Prompt-based Continual Learning
Probabilistic Prompt Distribution Learning for Animal Pose Estimation
Incorporating Pre-trained Model Prompting in Multimodal Stock Volume Movement Prediction
Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather Removal
Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning
PromptEHR: Conditional Electronic Healthcare Records Generation with Prompt Learning
Bayesian Prompt Learning for Image-Language Model Generalization
TeD-Loc: Text Distillation for Weakly Supervised Object Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.