《深度学习与计算机视觉》配套代码
本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
FusionBench: A Comprehensive Benchmark/Toolkit of Deep Model Fusion
AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR, 2024.
The is the official implementation of ICML 2023 paper "Revisiting Weighted Aggregation in Federated Learning with Neural Networks".
Representation Surgery for Multi-Task Model Merging. ICML, 2024.
Official repository of the "Transformer Fusion with Optimal Transport" paper, published as a conference paper at ICLR 2024.
Pack of LLMs: Model Fusion at Test-Time via Perplexity Optimization
SurgeryV2: Bridging the Gap Between Model Merging and Multi-Task Learning with Deep Representation Surgery. Arxiv, 2024.
This repository serves as a template for creating new projects based on FusionBench. It includes all the necessary configurations and boilerplate code to get started quickly.
Project for the course "Deep Learning" 2022 at ETH Zurich
Implementation for the paper "Copyright-Protected Language Generation via Adaptive Model Fusion"
[AAAI2025 (Oral)] PyTorch implementation of "Optimize Incompatible Parameters Through Compatibility-aware Knowledge Integration".
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