Toward Data Efficient Model Merging between Different Datasets without Performance Degradation
Fuente:
arXiv
Saved in:
| Main Authors: | Yamada, Masanori, Yamashita, Tomoya, Yamaguchi, Shin'ya, Chijiwa, Daiki |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Rationale-Enhanced Decoding for Multi-modal Chain-of-Thought
by: Yamaguchi, Shin'ya, et al.
Published: (2025)
by: Yamaguchi, Shin'ya, et al.
Published: (2025)
Zero-shot Concept Bottleneck Models
by: Yamaguchi, Shin'ya, et al.
Published: (2025)
by: Yamaguchi, Shin'ya, et al.
Published: (2025)
Parallel In-context Learning for Large Vision Language Models
by: Yamaguchi, Shin'ya, et al.
Published: (2026)
by: Yamaguchi, Shin'ya, et al.
Published: (2026)
Transfer Learning with Pre-trained Conditional Generative Models
by: Yamaguchi, Shin'ya, et al.
Published: (2022)
by: Yamaguchi, Shin'ya, et al.
Published: (2022)
Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks
by: Yamaguchi, Shin'ya, et al.
Published: (2024)
by: Yamaguchi, Shin'ya, et al.
Published: (2024)
Lossless Vocabulary Reduction for Auto-Regressive Language Models
by: Chijiwa, Daiki, et al.
Published: (2025)
by: Chijiwa, Daiki, et al.
Published: (2025)
Post-pre-training for Modality Alignment in Vision-Language Foundation Models
by: Yamaguchi, Shin'ya, et al.
Published: (2025)
by: Yamaguchi, Shin'ya, et al.
Published: (2025)
Explanation Bottleneck Models
by: Yamaguchi, Shin'ya, et al.
Published: (2024)
by: Yamaguchi, Shin'ya, et al.
Published: (2024)
Learning Robust Convolutional Neural Networks with Relevant Feature Focusing via Explanations
by: Adachi, Kazuki, et al.
Published: (2022)
by: Adachi, Kazuki, et al.
Published: (2022)
One-Shot Machine Unlearning with Mnemonic Code
by: Yamashita, Tomoya, et al.
Published: (2023)
by: Yamashita, Tomoya, et al.
Published: (2023)
Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
by: Chijiwa, Daiki, et al.
Published: (2025)
by: Chijiwa, Daiki, et al.
Published: (2025)
Evaluating Time-Series Training Dataset through Lens of Spectrum in Deep State Space Models
by: Kanai, Sekitoshi, et al.
Published: (2024)
by: Kanai, Sekitoshi, et al.
Published: (2024)
Test-time Adaptation for Regression by Subspace Alignment
by: Adachi, Kazuki, et al.
Published: (2024)
by: Adachi, Kazuki, et al.
Published: (2024)
Do We Really Need Permutations? Impact of Model Width on Linear Mode Connectivity
by: Ito, Akira, et al.
Published: (2025)
by: Ito, Akira, et al.
Published: (2025)
Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation
by: Takahashi, Hiroshi, et al.
Published: (2025)
by: Takahashi, Hiroshi, et al.
Published: (2025)
The Strong Lottery Ticket Hypothesis for Multi-Head Attention Mechanisms
by: Otsuka, Hikari, et al.
Published: (2025)
by: Otsuka, Hikari, et al.
Published: (2025)
Fine-Tuning without Performance Degradation
by: Wang, Han, et al.
Published: (2025)
by: Wang, Han, et al.
Published: (2025)
Understanding Pure Textual Reasoning for Blind Image Quality Assessment
by: Li, Yuan, et al.
Published: (2026)
by: Li, Yuan, et al.
Published: (2026)
Machine Learning Modeling for Multi-order Human Visual Motion Processing
by: Sun, Zitang, et al.
Published: (2025)
by: Sun, Zitang, et al.
Published: (2025)
Merge to Mix: Mixing Datasets via Model Merging
by: Tao, Zhixu Silvia, et al.
Published: (2025)
by: Tao, Zhixu Silvia, et al.
Published: (2025)
Merging Smarter, Generalizing Better: Enhancing Model Merging on OOD Data
by: Zhang, Bingjie, et al.
Published: (2025)
by: Zhang, Bingjie, et al.
Published: (2025)
Difference Vector Equalization for Robust Fine-tuning of Vision-Language Models
by: Suzuki, Satoshi, et al.
Published: (2025)
by: Suzuki, Satoshi, et al.
Published: (2025)
MergeIT: From Selection to Merging for Efficient Instruction Tuning
by: Cai, Hongyi, et al.
Published: (2025)
by: Cai, Hongyi, et al.
Published: (2025)
Covariance-aware Feature Alignment with Pre-computed Source Statistics for Test-time Adaptation to Multiple Image Corruptions
by: Adachi, Kazuki, et al.
Published: (2022)
by: Adachi, Kazuki, et al.
Published: (2022)
Toward a Holistic Approach to Continual Model Merging
by: Phan, Hoang, et al.
Published: (2025)
by: Phan, Hoang, et al.
Published: (2025)
MergeMix: Optimizing Mid-Training Data Mixtures via Learnable Model Merging
by: Wang, Jiapeng, et al.
Published: (2026)
by: Wang, Jiapeng, et al.
Published: (2026)
MIN-Merging: Merge the Important Neurons for Model Merging
by: Liang, Yunfei
Published: (2025)
by: Liang, Yunfei
Published: (2025)
Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
by: Cho, Yeseul, et al.
Published: (2025)
by: Cho, Yeseul, et al.
Published: (2025)
Merging Text Transformer Models from Different Initializations
by: Verma, Neha, et al.
Published: (2024)
by: Verma, Neha, et al.
Published: (2024)
HAPI: A Model for Learning Robot Facial Expressions from Human Preferences
by: Yang, Dongsheng, et al.
Published: (2025)
by: Yang, Dongsheng, et al.
Published: (2025)
Towards Effective and Efficient Graph Alignment without Supervision
by: Chen, Songyang, et al.
Published: (2026)
by: Chen, Songyang, et al.
Published: (2026)
Partially Frozen Random Networks Contain Compact Strong Lottery Tickets
by: Otsuka, Hikari, et al.
Published: (2024)
by: Otsuka, Hikari, et al.
Published: (2024)
Towards Modeling Data Quality and Machine Learning Model Performance
by: Anjum, Usman, et al.
Published: (2024)
by: Anjum, Usman, et al.
Published: (2024)
Towards Causal Relationship in Indefinite Data: Baseline Model and New Datasets
by: Chen, Hang, et al.
Published: (2024)
by: Chen, Hang, et al.
Published: (2024)
Guided Model Merging for Hybrid Data Learning: Leveraging Centralized Data to Refine Decentralized Models
by: Zhu, Junyi, et al.
Published: (2025)
by: Zhu, Junyi, et al.
Published: (2025)
FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization
by: Chen, Hao Mark, et al.
Published: (2025)
by: Chen, Hao Mark, et al.
Published: (2025)
PSO-Merging: Merging Models Based on Particle Swarm Optimization
by: Zhang, Kehao, et al.
Published: (2025)
by: Zhang, Kehao, et al.
Published: (2025)
Bayesian Model Merging
by: Li, Kaiyang, et al.
Published: (2026)
by: Li, Kaiyang, et al.
Published: (2026)
A Novel Hierarchical Integration Method for Efficient Model Merging in Medical LLMs
by: Timilsina, Prakrit, et al.
Published: (2025)
by: Timilsina, Prakrit, et al.
Published: (2025)
Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging
by: Yang, Jinluan, et al.
Published: (2025)
by: Yang, Jinluan, et al.
Published: (2025)
Similar Items
-
Rationale-Enhanced Decoding for Multi-modal Chain-of-Thought
by: Yamaguchi, Shin'ya, et al.
Published: (2025) -
Zero-shot Concept Bottleneck Models
by: Yamaguchi, Shin'ya, et al.
Published: (2025) -
Parallel In-context Learning for Large Vision Language Models
by: Yamaguchi, Shin'ya, et al.
Published: (2026) -
Transfer Learning with Pre-trained Conditional Generative Models
by: Yamaguchi, Shin'ya, et al.
Published: (2022) -
Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks
by: Yamaguchi, Shin'ya, et al.
Published: (2024)