Copertina

Caption, Create, Continue: Continual Learning with Pre-trained Generative Vision-Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Solomon, Indu, Aung, Aye Phyu Phyu, Kumar, Uttam, Jayavelu, Senthilnath
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

U-TELL: Unsupervised Task Expert Lifelong Learning
di: Solomon, Indu, et al.
Pubblicazione: (2024)

XMOL: Explainable Multi-property Optimization of Molecules
di: Aung, Aye Phyu Phyu, et al.
Pubblicazione: (2024)

Double Oracle Neural Architecture Search for Game Theoretic Deep Learning Models
di: Aung, Aye Phyu Phyu, et al.
Pubblicazione: (2024)

Self-evolving Autoencoder Embedded Q-Network
di: Senthilnath, J., et al.
Pubblicazione: (2024)

Physics Informed Generative Models for Magnetic Field Images
di: Aung, Aye Phyu Phyu, et al.
Pubblicazione: (2025)

TS-HINT: Enhancing Semiconductor Time Series Regression Using Attention Hints From Large Language Model Reasoning
di: Rico, Jonathan Adam, et al.
Pubblicazione: (2025)

A Spatial-Physics Informed Model for 3D Spiral Sample Scanned by SQUID Microscopy
di: Senthilnath, J., et al.
Pubblicazione: (2025)

Compound Fault Diagnosis for Train Transmission Systems Using Deep Learning with Fourier-enhanced Representation
di: Rico, Jonathan Adam, et al.
Pubblicazione: (2025)

Incremental Multistep Forecasting of Battery Degradation Using Pseudo Targets
di: Rico, Jonathan Adam, et al.
Pubblicazione: (2025)

Robust Representation Learning with Self-Distillation for Domain Generalization
di: Singh, Ankur, et al.
Pubblicazione: (2023)

On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-trained Language Models of Code
di: Weyssow, Martin, et al.
Pubblicazione: (2023)

Towards a General Framework for Continual Learning with Pre-training
di: Wang, Liyuan, et al.
Pubblicazione: (2023)

Practical Continual Forgetting for Pre-trained Vision Models
di: Zhao, Hongbo, et al.
Pubblicazione: (2025)

The final size and critical times of an SIVR epidemic model
di: Win, Phyu Phyu, et al.
Pubblicazione: (2024)

CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models
di: Chen, Shengzhuang, et al.
Pubblicazione: (2025)

Realistic Continual Learning Approach using Pre-trained Models
di: Nasri, Nadia, et al.
Pubblicazione: (2024)

Do Pre-trained Models Benefit Equally in Continual Learning?
di: Lee, Kuan-Ying, et al.
Pubblicazione: (2022)

Efficient Continual Pre-training of LLMs for Low-resource Languages
di: Nag, Arijit, et al.
Pubblicazione: (2024)

Simple and Scalable Strategies to Continually Pre-train Large Language Models
di: Ibrahim, Adam, et al.
Pubblicazione: (2024)

VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Vision Backbones
di: Shen, Lefei, et al.
Pubblicazione: (2025)

Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning
di: Wang, Huiyi, et al.
Pubblicazione: (2024)

RanPAC: Random Projections and Pre-trained Models for Continual Learning
di: McDonnell, Mark D., et al.
Pubblicazione: (2023)

Navigating Ethical Review Processes in Conflict‐Affected, Authoritarian Contexts: A Case Study of Myanmar's Interim Ethics Review Board ( IERB )
di: Phyu Phyu Thin Zaw, et al.
Pubblicazione: (2026)

C-LoRA: Continual Low-Rank Adaptation for Pre-trained Models
di: Zhang, Xin, et al.
Pubblicazione: (2025)

Towards General Continuous Memory for Vision-Language Models
di: Wu, Wenyi, et al.
Pubblicazione: (2025)

CMR Scaling Law: Predicting Critical Mixture Ratios for Continual Pre-training of Language Models
di: Gu, Jiawei, et al.
Pubblicazione: (2024)

Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation
di: Zhu, Jianghan, et al.
Pubblicazione: (2025)

Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model
di: Shi, Jiang-Xin, et al.
Pubblicazione: (2024)

Beyond Cosine Decay: On the effectiveness of Infinite Learning Rate Schedule for Continual Pre-training
di: Singh, Vaibhav, et al.
Pubblicazione: (2025)

Learning to Rank Pre-trained Vision-Language Models for Downstream Tasks
di: Ding, Yuhe, et al.
Pubblicazione: (2024)

Extinction, persistence and growing in a degenerate logistic model with impulses
di: Cintra, Willian, et al.
Pubblicazione: (2024)

Learning Dynamics in Continual Pre-Training for Large Language Models
di: Wang, Xingjin, et al.
Pubblicazione: (2025)

LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning
di: Peng, Liangzu, et al.
Pubblicazione: (2024)

Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code
di: Nakamura, Taishi, et al.
Pubblicazione: (2024)

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement
di: Rao, Zhefan, et al.
Pubblicazione: (2024)

S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training
di: Hu, Yuezhou, et al.
Pubblicazione: (2024)

Adapting Multilingual LLMs to Low-Resource Languages using Continued Pre-training and Synthetic Corpus
di: Joshi, Raviraj, et al.
Pubblicazione: (2024)

Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training
di: Yang, Kailai, et al.
Pubblicazione: (2025)

Domain-Adaptive Continued Pre-Training of Small Language Models
di: Faroz, Salman
Pubblicazione: (2025)

Pre-trained Vision-Language Models Learn Discoverable Visual Concepts
di: Zang, Yuan, et al.
Pubblicazione: (2024)