Copertina

LEARN: A Unified Framework for Multi-Task Domain Adapt Few-Shot Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ravichandran, Bharadwaj, Lynch, Alexander, Brockman, Sarah, RichardWebster, Brandon, Du, Dawei, Hoogs, Anthony, Funk, Christopher
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Steerable Pluralism: Pluralistic Alignment via Few-Shot Comparative Regression
di: Adams, Jadie, et al.
Pubblicazione: (2025)

ALIGN: Prompt-based Attribute Alignment for Reliable, Responsible, and Personalized LLM-based Decision-Making
di: Ravichandran, Bharadwaj, et al.
Pubblicazione: (2025)

Enhancing Ecological Monitoring with Multi-Objective Optimization: A Novel Dataset and Methodology for Segmentation Algorithms
di: Abraham, Sophia J., et al.
Pubblicazione: (2024)

Adapting In-Domain Few-Shot Segmentation to New Domains without Source Domain Retraining
di: Fan, Qi, et al.
Pubblicazione: (2025)

Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation
di: Chi, Zhixiang, et al.
Pubblicazione: (2025)

Adapt Before Comparison: A New Perspective on Cross-Domain Few-Shot Segmentation
di: Herzog, Jonas
Pubblicazione: (2024)

Task-Specific Preconditioner for Cross-Domain Few-Shot Learning
di: Kang, Suhyun, et al.
Pubblicazione: (2024)

Task-Level Contrastiveness for Cross-Domain Few-Shot Learning
di: Topollai, Kristi, et al.
Pubblicazione: (2025)

FS-DAG: Few Shot Domain Adapting Graph Networks for Visually Rich Document Understanding
di: Agarwal, Amit, et al.
Pubblicazione: (2025)

A Domain-Adapted Lightweight Ensemble for Resource-Efficient Few-Shot Plant Disease Classification
di: Islam, Anika, et al.
Pubblicazione: (2025)

What should we be worried about? : real scenarios that keep scientists up at night / John Brockman
di: Brockman, John
Pubblicazione: (2014)

Aligning Machiavellian Agents: Behavior Steering via Test-Time Policy Shaping
di: Mujtaba, Dena, et al.
Pubblicazione: (2025)

Few-Shot Task Learning through Inverse Generative Modeling
di: Netanyahu, Aviv, et al.
Pubblicazione: (2024)

AdaptAgent: Adapting Multimodal Web Agents with Few-Shot Learning from Human Demonstrations
di: Verma, Gaurav, et al.
Pubblicazione: (2024)

PULSE: A Unified Multi-Task Architecture for Cardiac Segmentation, Diagnosis, and Few-Shot Cross-Modality Clinical Adaptation
di: Ghouse, Hania, et al.
Pubblicazione: (2025)

MCLRL: A Multi-Domain Contrastive Learning with Reinforcement Learning Framework for Few-Shot Modulation Recognition
di: Xu, Dongwei, et al.
Pubblicazione: (2025)

Flora of Mount Rainier National Park / C. Frank, Brockman (Christian Frank)
di: Brockman, C. Frank
Pubblicazione: (1947)

The Assessment of Library Performance. An Australian Perspective of the British Inter-Library Comparison Project.
di: Brockman, J. R.
Pubblicazione: (1984)

Textual and Visual Guided Task Adaptation for Source-Free Cross-Domain Few-Shot Segmentation
di: Liu, Jianming, et al.
Pubblicazione: (2025)

A Multi-Port Concurrent Communication Model for handling Compute Intensive Tasks on Distributed Satellite System Constellations
di: Veeravalli, Bharadwaj
Pubblicazione: (2026)

MTMD: A Multi-Task Multi-Domain Framework for Unified Ad Lightweight Ranking at Pinterest
di: Yang, Xiao, et al.
Pubblicazione: (2025)

Domain-Rectifying Adapter for Cross-Domain Few-Shot Segmentation
di: Su, Jiapeng, et al.
Pubblicazione: (2024)

Learning Multi-Modal Prototypes for Cross-Domain Few-Shot Object Detection
di: Wang, Wanqi, et al.
Pubblicazione: (2026)

Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering
di: Chen, Mingda, et al.
Pubblicazione: (2023)

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation
di: Nie, Jiahao, et al.
Pubblicazione: (2026)

SD-FSMIS: Adapting Stable Diffusion for Few-Shot Medical Image Segmentation
di: Li, Meihua, et al.
Pubblicazione: (2026)

Learning to Adapt Category Consistent Meta-Feature of CLIP for Few-Shot Classification
di: Shi, Jiaying, et al.
Pubblicazione: (2024)

Adapting Foundation Models for Few-Shot Medical Image Segmentation: Actively and Sequentially
di: Yang, Jingyun, et al.
Pubblicazione: (2025)

MVP-Shot: Multi-Velocity Progressive-Alignment Framework for Few-Shot Action Recognition
di: Qu, Hongyu, et al.
Pubblicazione: (2024)

Review of Zero-Shot and Few-Shot AI Algorithms in The Medical Domain
di: Badawi, Maged, et al.
Pubblicazione: (2024)

Few-Shot Synthetic Data Generation with Diffusion Models for Downstream Vision Tasks
di: Dushenev, Daniil, et al.
Pubblicazione: (2026)

Meta-Task: A Method-Agnostic Framework for Learning to Regularize in Few-Shot Learning
di: Rostami, Mohammad, et al.
Pubblicazione: (2024)

Few-Shot Precise Event Spotting via Unified Multi-Entity Graph and Distillation
di: Liu, Zhaoyu, et al.
Pubblicazione: (2025)

Video-to-Task Learning via Motion-Guided Attention for Few-Shot Action Recognition
di: Guo, Hanyu, et al.
Pubblicazione: (2024)

A Mixture-of-Experts Approach to Few-Shot Task Transfer in Open-Ended Text Worlds
di: Cui, Christopher Z., et al.
Pubblicazione: (2024)

Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation
di: Röder, Manuel, et al.
Pubblicazione: (2025)

Few-Shot Domain Adaptation for Learned Image Compression
di: Zhang, Tianyu, et al.
Pubblicazione: (2024)

Random Registers for Cross-Domain Few-Shot Learning
di: Yi, Shuai, et al.
Pubblicazione: (2025)

Few-Shot Adaptation of Grounding DINO for Agricultural Domain
di: Singh, Rajhans, et al.
Pubblicazione: (2025)

Few-Shot Demonstration-Driven Task Coordination and Trajectory Execution for Multi-Robot Systems
di: Kim, Taehyeon, et al.
Pubblicazione: (2025)