Model Merge
Model Merge is a methodological contribution in machine learning research that integrates multiple pre-trained models into a unified architecture by systematically combining their parameters, representations, or outputs to enhance performance, generalization, or efficiency.
40
Publications
2.1K
Citations
133
Authors
66
Institutions
Publications per year
2017–2026
17
Parents
40
Business Process Model Merging
Marcello La Rosa, Marlon Dumas, Reina Uba et al. · ACM Transactions on Software Engineering and Methodology · 2013 · 201 citations · Full text
Business, Information Systems, Management Information Systems +15
Greg Brunet, Marsha Chećhik, Steve Easterbrook et al. · 2006 · 128 citations
Engineering, Systems Engineering, Knowledge Representation +12
1–5 of 40
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International Computer Science Institute, United States
2 publications · 157 citations
2
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1–5 of 133
66

University of Toronto
Toronto, Canada
3 h-index
10 publications
998 citations

International Computer Science Institute
Berkeley, United States
2 h-index
3 publications
272 citations
University of Michigan
Ann Arbor, United States
2 h-index
5 publications
156 citations

Imperial College London
London, United Kingdom
2 h-index
2 publications
83 citations

University of Auckland
Auckland, New Zealand
1 h-index
1 publications
30 citations
University of Washington
Seattle, United States
1 h-index
1 publications
30 citations

The University of Melbourne
Melbourne, Australia
1 h-index
1 publications
30 citations
Research Center for Information Technology Innovation, Academia Sinica
Taipei, Taiwan
1 h-index
4 publications
116 citations
1–8 of 66
Repository · 4 publications · 146 citations
4
h-index
1 publications · 19 citations
1
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1 publications · 11 citations
1
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SoSyM · 1 publications · 38 citations
1
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JOSS · 1 publications · 64 citations
1
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1–5