FeatCal: Feature Calibration for Post-Merging Models

arXiv:2605.13030 · cs.LG, cs.AI · Submitted 2026-05-13 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-05-13

Updated: 2026-10-08

Code: https://github.com/egangu/featcal

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Calibration — 4× in this paper · explained in 7 episodes
• Model Merging — 2× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes

Sources

• SurgeryV2: Bridging the Gap Between Model Merging and Multi-Task Learning with Deep Representation Surgery
• RegMean++: Enhancing Effectiveness and Generalization of Regression Mean for Model Merging
• MergeBench: A Benchmark for Merging Domain-Specialized LLMs
• Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
• Model Merging Scaling Laws in Large Language Models
• MergePipe: A Budget-Aware Parameter Management System for Scalable LLM Merging
• InfiFPO: Implicit Model Fusion via Preference Optimization in Large Language Models
• InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion
• InfiCoEvalChain: A Blockchain-Based Decentralized Framework for Collaborative LLM Evaluation
• A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models

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