Papers › Git Re-Basin: Merging Models modulo Permutation Symmetries

Git Re-Basin: Merging Models modulo Permutation Symmetries

11 Sep 2022arXiv:2209.04836archive 2025-07-28

Samuel K. Ainsworth, Jonathan Hayase, Siddhartha Srinivasa

The success of deep learning is due in large part to our ability to solve certain massive non-convex optimization problems with relative ease. Though non-convex optimization is NP-hard, simple algorithms -- often variants of stochastic gradient descent -- exhibit surprising effectiveness in fitting large neural networks in practice. We argue that neural network loss landscapes often contain (nearly) a single basin after accounting for all possible permutation symmetries of hidden units a la Entezari et al. 2021. We introduce three algorithms to permute the units of one model to bring them into alignment with a reference model in order to merge the two models in weight space. This transformation produces a functionally equivalent set of weights that lie in an approximately convex basin near the reference model. Experimentally, we demonstrate the single basin phenomenon across a variety of model architectures and datasets, including the first (to our knowledge) demonstration of zero-barrier linear mode connectivity between independently trained ResNet models on CIFAR-10. Additionally, we identify intriguing phenomena relating model width and training time to mode connectivity. Finally, we discuss shortcomings of the linear mode connectivity hypothesis, including a counterexample to the single basin theory.

PaperPDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2209.04836")

Code

Syntology Ran 6 of 6 code samples harvested from 2 repositories linked to this paper; 0 have no recorded run. Of those that ran: 1 ran · honoured contract; 5 ran · our draft was wrong.

By repository: official repository: 5 samples from 1 repository, 5 ran; community (archive-listed): 1 sample from 1 repository, 1 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

samuela/git-re-basin officialmentioned in papermentioned on GitHubjax report
gg-Dema/Git_merge mentioned on GitHubpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

6 samples harvested; 6 ran; 1 honoured the contract we drafted; 0 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

1ran · honoured contract
5ran · our draft was wrong

Licence: 0 of the 6 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from 2 repositories linked to this paper, official or community; each sample names its own and says which. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

get_permuted_param samuela/git-re-basin/src/weight_matching.py official repository ran · honoured contract MIT (permissive) · 7a670f479fecf6dc · report
mlp_permutation_spec samuela/git-re-basin/src/weight_matching.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · 1817b5650fd28afd · report
permutation_spec_from_axes_to_perm samuela/git-re-basin/src/weight_matching.py official repository ran · our draft was wrong MIT (permissive) · 602ebbf2f53305ff · report
plot_interp_acc samuela/git-re-basin/src/cifar10_mlp_weight_matching.py official repository ran · our draft was wrong MIT (permissive) · a6b09bc64f436279 · report
plot_interp_loss samuela/git-re-basin/src/cifar10_mlp_weight_matching.py official repository ran · our draft was wrong MIT (permissive) · 0494520c0147c1e8 · report
conv3x3 themrzmaster/git-re-basin-pytorch/models/resnet.py community (archive-listed) ran · our draft was wrong MIT (permissive) · 583f9780bdd00a45 · report

Tasks

Linear Mode ConnectivityRe-basin

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Methods

1x1 ConvolutionAverage PoolingBatch NormalizationBottleneck Residual BlockConvolutionGlobal Average PoolingKaiming InitializationMax PoolingReLUResidual BlockResidual Connection

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections