Papers with Code 아카이브

Prompt Learning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ljaiverson/pfedmoap

공식 코드

Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models

https://github.com/lmsdss/IPO

공식 코드

IPO: Interpretable Prompt Optimization for Vision-Language Models

https://github.com/longlongaaago/vspbfr

공식 코드

Visual Style Prompt Learning Using Diffusion Models for Blind Face Restoration

https://github.com/longquanjiang/ontoscprompt

공식 코드

Ontology-Guided, Hybrid Prompt Learning for Generalization in Knowledge Graph Question Answering

https://github.com/longzilicart/pip_universal

공식 코드

Prompt-In-Prompt Learning for Universal Image Restoration

https://github.com/louisegan514/hidden-entity-detection-from-github-leveraging-llms

공식 코드

Hidden Entity Detection from GitHub Leveraging Large Language Models

https://github.com/lsh-ahu/icpl-reid

공식 코드

ICPL-ReID: Identity-Conditional Prompt Learning for Multi-Spectral Object Re-Identification

https://github.com/lts5/slip

공식 코드

Slide-Level Prompt Learning with Vision Language Models for Few-Shot Multiple Instance Learning in Histopathology

https://github.com/ltttpku/cmmp

공식 코드

Exploring Conditional Multi-Modal Prompts for Zero-shot HOI Detection

https://github.com/lxasqjc/mcpl

공식 코드

An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning

https://github.com/ma-kjh/CMA-OoDD

공식 코드

Enhanced OoD Detection through Cross-Modal Alignment of Multi-Modal Representations

https://github.com/mainaksingha01/AD-CLIP

공식 코드

AD-CLIP: Adapting Domains in Prompt Space Using CLIP

https://github.com/mainaksingha01/applenet

공식 코드

APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIP

https://github.com/mainaksingha01/gopro

공식 코드

GOPro: Generate and Optimize Prompts in CLIP using Self-Supervised Learning

https://github.com/mainaksingha01/odg-clip

공식 코드

Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalization

https://github.com/mainaksingha01/splip

공식 코드

Elevating All Zero-Shot Sketch-Based Image Retrieval Through Multimodal Prompt Learning

https://github.com/mala-lab/faprompt

공식 코드

Fine-grained Abnormality Prompt Learning for Zero-shot Anomaly Detection

https://github.com/mala-lab/negprompt

공식 코드

Learning Transferable Negative Prompts for Out-of-Distribution Detection

https://github.com/mala-lab/sic-cads

공식 코드

Simple Image-level Classification Improves Open-vocabulary Object Detection

https://github.com/mala-lab/tpp

공식 코드

Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach

https://github.com/marclafon/gallop

공식 코드

GalLoP: Learning Global and Local Prompts for Vision-Language Models

https://github.com/mariodoebler/test-time-adaptation

공식 코드

A Lost Opportunity for Vision-Language Models: A Comparative Study of Online Test-Time Adaptation for Vision-Language Models

https://github.com/mashengkun/cpl

공식 코드

Making Pre-trained Language Models Better Continual Few-Shot Relation Extractors

https://github.com/maxzanella/mta

공식 코드

On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?

https://github.com/mcg-nju/provp

공식 코드

Progressive Visual Prompt Learning with Contrastive Feature Re-formation

https://github.com/megvii-research/caspl

공식 코드

Cascade Prompt Learning for Vision-Language Model Adaptation

https://github.com/miccaiif/top

공식 코드

The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification

https://github.com/miccunifi/kdpl

공식 코드

Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation

https://github.com/mikegu721/gapo

공식 코드

GAPO: Learning Preferential Prompt through Generative Adversarial Policy Optimization

https://github.com/minhanh151/pre

공식 코드

PRE: Vision-Language Prompt Learning with Reparameterization Encoder

https://github.com/minhanh151/respro

공식 코드

PRE: Vision-Language Prompt Learning with Reparameterization Encoder

https://github.com/ml-stat-Sustech/CLIP_Calibration

공식 코드

Open-Vocabulary Calibration for Fine-tuned CLIP

https://github.com/mlvlab/prometar

공식 코드

Prompt Learning via Meta-Regularization

https://github.com/moatifbutt/color-peel

공식 코드

ColorPeel: Color Prompt Learning with Diffusion Models via Color and Shape Disentanglement

https://github.com/mrflogs/iclr24

공식 코드

A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation

https://github.com/mrwu-mac/controlmllm

공식 코드

ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language Models

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.