{ "schema_version": 1, "title": "Reproduction: Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation", "emoji": "🎯", "space_id": "deepakgudla/fusion-repro", "paper": { "arxiv_id": "2605.22350" }, "tags": [ "icml2026-repro", "paper-lvRLG6C0zZ" ], "updated_at": "2026-07-23T09:33:44+00:00", "root": { "slug": "index", "title": "Reproduction: Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation", "file": "pages/index.md", "children": [ { "slug": "executive-summary", "title": "Executive Summary", "file": "pages/executive-summary/page.md", "children": [] }, { "slug": "claim-1-partial-fusion-interpolation-eq-3", "title": "Claim 1: Partial Fusion Interpolation (Eq. 3)", "file": "pages/claim-1-partial-fusion-interpolation-eq-3/page.md", "children": [] }, { "slug": "claim-2-efficient-tradeoff-1-45x-params", "title": "Claim 2: Efficient Tradeoff (~1.45x Params)", "file": "pages/claim-2-efficient-tradeoff-1-45x-params/page.md", "children": [] }, { "slug": "claim-3-mlp-fine-tuning-table-1", "title": "Claim 3: MLP Fine-tuning (Table 1)", "file": "pages/claim-3-mlp-fine-tuning-table-1/page.md", "children": [] }, { "slug": "claim-4-cnn-fine-tuning-table-1", "title": "Claim 4: CNN Fine-tuning (Table 1)", "file": "pages/claim-4-cnn-fine-tuning-table-1/page.md", "children": [] }, { "slug": "claim-5-clustering-vs-unstructured-pruning-figure-9", "title": "Claim 5: Clustering vs Unstructured Pruning (Figure 9)", "file": "pages/claim-5-clustering-vs-unstructured-pruning-figure-9/page.md", "children": [] }, { "slug": "claim-6-fixed-layer-partial-fusion-figure-7", "title": "Claim 6: Fixed-Layer Partial Fusion (Figure 7)", "file": "pages/claim-6-fixed-layer-partial-fusion-figure-7/page.md", "children": [] }, { "slug": "conclusion", "title": "Conclusion", "file": "pages/conclusion/page.md", "children": [] }, { "slug": "fusion-repro", "title": "fusion-repro", "file": "pages/fusion-repro/page.md", "children": [] } ] }, "agent_view_tokens": 3790, "revision": "1784799224803636109" }