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Model Merging

552 directly classified papers

Papers per year

Papers

Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning NIPS 2024
Parameter Competition Balancing for Model Merging NIPS 2024
Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging NIPS 2024
$C^2M^3$: Cycle-Consistent Multi-Model Merging NIPS 2024
Post-Hoc Reversal: Are We Selecting Models Prematurely? NIPS 2024
Consistent Joint Decision-Making with Heterogeneous Learning Models EACL 2024
Backward Compatibility During Data Updates by Weight Interpolation EACL 2024
EURECOM at SemEval-2024 Task 4: Hierarchical Loss and Model Ensembling in Detecting Persuasion Techniques SEMEVAL 2024
Mind’s Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models NAACL 2024
Bridging the Gap between Different Vocabularies for LLM Ensemble NAACL 2024
When Quantization Affects Confidence of Large Language Models? NAACL 2024
DEM: Distribution Edited Model for Training with Mixed Data Distributions EMNLP 2024
Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning ACL 2024
Ensemble Learning for Heterogeneous Large Language Models with Deep Parallel Collaboration NIPS 2024
A Practitioner's Guide to Real-World Continual Multimodal Pretraining NIPS 2024
AdaMerging: Adaptive Model Merging for Multi-Task Learning ICLR 2024
Deep Graph Mating NIPS 2024
How Far Can We Compress Instant-NGP-Based NeRF? CVPR 2024
MEFT: Memory-Efficient Fine-Tuning through Sparse Adapter ACL 2024
Unlocking the Potential of Global Human Expertise NIPS 2024
Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems NIPS 2024
EMR-Merging: Tuning-Free High-Performance Model Merging NIPS 2024
ReFACT: Updating Text-to-Image Models by Editing the Text Encoder NAACL 2024
David helps Goliath: Inference-Time Collaboration Between Small Specialized and Large General Diffusion LMs NAACL 2024
EURECOM at SemEval-2024 Task 4: Hierarchical Loss and Model Ensembling in Detecting Persuasion Techniques NAACL 2024