Cover Image

UNIFORM: Unifying Knowledge from Large-scale and Diverse Pre-trained Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Yimu, Zhuang, Weiming, Chen, Chen, Huang, Jiabo, Li, Jingtao, Lyu, Lingjuan
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Replay-Free Continual Low-Rank Adaptation with Dynamic Memory
by: Chen, Huancheng, et al.
Published: (2024)

Closer to Reality: Practical Semi-Supervised Federated Learning for Foundation Model Adaptation
by: Sun, Guangyu, et al.
Published: (2025)

FEDEXCHANGE: Bridging the Domain Gap in Federated Object Detection for Free
by: Yuan, Haolin, et al.
Published: (2025)

UniCompress: Token Compression for Unified Vision-Language Understanding and Generation
by: Wang, Ziyao, et al.
Published: (2026)

Towards Fundamentally Scalable Model Selection: Asymptotically Fast Update and Selection
by: Wang, Wenxiao, et al.
Published: (2024)

VibeToken: Scaling 1D Image Tokenizers and Autoregressive Models for Dynamic Resolution Generations
by: Patel, Maitreya, et al.
Published: (2026)

Seeing Further on the Shoulders of Giants: Knowledge Inheritance for Vision Foundation Models
by: Huang, Jiabo, et al.
Published: (2025)

FedWon: Triumphing Multi-domain Federated Learning Without Normalization
by: Zhuang, Weiming, et al.
Published: (2023)

ExpVG: Investigating the Design Space of Visual Grounding in Multimodal Large Language Model
by: Kang, Weitai, et al.
Published: (2025)

On the Limits of Token Reduction for Efficient Unified Vision Language Training
by: Chen, Siyi, et al.
Published: (2026)

Empirical Recipes for Efficient and Compact Vision-Language Models
by: Huang, Jiabo, et al.
Published: (2026)

Training-Free Layout-to-Image Generation with Marginal Attention Constraints
by: Chen, Huancheng, et al.
Published: (2024)

COALA: A Practical and Vision-Centric Federated Learning Platform
by: Zhuang, Weiming, et al.
Published: (2024)

Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget
by: Sehwag, Vikash, et al.
Published: (2024)

Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery
by: Liu, Mingxuan, et al.
Published: (2023)

DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models
by: Wang, Zhenting, et al.
Published: (2023)

A Simple Background Augmentation Method for Object Detection with Diffusion Model
by: Li, Yuhang, et al.
Published: (2024)

How to Trace Latent Generative Model Generated Images without Artificial Watermark?
by: Wang, Zhenting, et al.
Published: (2024)

Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models
by: Luo, Weijian, et al.
Published: (2023)

Quantum-Gated Task-interaction Knowledge Distillation for Pre-trained Model-based Class-Incremental Learning
by: Li, Linjie, et al.
Published: (2026)

Multimodal Autoregressive Pre-training of Large Vision Encoders
by: Fini, Enrico, et al.
Published: (2024)

Incorporating Pre-trained Diffusion Models in Solving the Schrödinger Bridge Problem
by: Tang, Zhicong, et al.
Published: (2025)

Towards Large-scale Chemical Reaction Image Parsing via a Multimodal Large Language Model
by: Chen, Yufan, et al.
Published: (2025)

Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
by: Lai, Zhengfeng, et al.
Published: (2024)

Split Adaptation for Pre-trained Vision Transformers
by: Wang, Lixu, et al.
Published: (2025)

Shortcutting Pre-trained Flow Matching Diffusion Models is Almost Free Lunch
by: Cai, Xu, et al.
Published: (2025)

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

Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers
by: Wang, Lirui, et al.
Published: (2024)

Unified Framework for Pre-trained Neural Network Compression via Decomposition and Optimized Rank Selection
by: Aghababaei-Harandi, Ali, et al.
Published: (2024)

Dataset Ownership Verification in Contrastive Pre-trained Models
by: Xie, Yuechen, et al.
Published: (2025)

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

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

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

Enhancing Pre-trained Representation Classifiability can Boost its Interpretability
by: Shen, Shufan, et al.
Published: (2025)

Slight Corruption in Pre-training Data Makes Better Diffusion Models
by: Chen, Hao, et al.
Published: (2024)

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction
by: Duan, Chen-Long, et al.
Published: (2024)

Epistemic Uncertainty Quantification For Pre-trained Neural Network
by: Wang, Hanjing, et al.
Published: (2024)

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

Machine Unlearning on Pre-trained Models by Residual Feature Alignment Using LoRA
by: Qin, Laiqiao, et al.
Published: (2024)

Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation
by: Ma, Jiabo, et al.
Published: (2024)