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| { | |
| "schema_version": 1, | |
| "title": "Repro - Neural Thickets (tinygrad)", | |
| "emoji": "🎯", | |
| "space_id": "ofou/Repro-Neural-Thickets", | |
| "paper": { | |
| "arxiv_id": "2603.12228", | |
| "openreview_id": "92oF5bU4cU", | |
| "title": "Neural Thickets: Diverse Task Experts Are Dense Around Pretrained Weights", | |
| "icml_pid": "3715" | |
| }, | |
| "tags": [ | |
| "icml2026-repro", | |
| "paper-92oF5bU4cU" | |
| ], | |
| "updated_at": "2026-07-15T20:27:32+00:00", | |
| "root": { | |
| "slug": "index", | |
| "title": "Repro - Neural Thickets (tinygrad)", | |
| "file": "pages/index.md", | |
| "children": [ | |
| { | |
| "slug": "claim-1-dense-task-expert-neighborhoods-emerge-at-scale-needle-vs-thicket", | |
| "title": "Claim 1: Dense task-expert neighborhoods emerge at scale (needle vs thicket)", | |
| "file": "pages/claim-1-dense-task-expert-neighborhoods-emerge-at-scale-needle-vs-thicket/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-2-qwen2-5-solution-density-and-diversity-increase-with-scale", | |
| "title": "Claim 2: Qwen2.5 solution density and diversity increase with scale", | |
| "file": "pages/claim-2-qwen2-5-solution-density-and-diversity-increase-with-scale/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-3-random-perturbations-are-task-specialists-not-generalists", | |
| "title": "Claim 3: Random perturbations are task specialists, not generalists", | |
| "file": "pages/claim-3-random-perturbations-are-task-specialists-not-generalists/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-4-randopt-matches-or-exceeds-ppo-grpo-es-in-many-llm-post-training-settings", | |
| "title": "Claim 4: RandOpt matches or exceeds PPO/GRPO/ES in many LLM post-training settings", | |
| "file": "pages/claim-4-randopt-matches-or-exceeds-ppo-grpo-es-in-many-llm-post-training-settings/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-5-randopt-accuracy-scales-with-population-size-and-pretrained-model-scale", | |
| "title": "Claim 5: RandOpt accuracy scales with population size and pretrained model scale", | |
| "file": "pages/claim-5-randopt-accuracy-scales-with-population-size-and-pretrained-model-scale/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "conclusion", | |
| "title": "Conclusion", | |
| "file": "pages/conclusion/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "neural-thickets-repro", | |
| "title": "neural-thickets-repro", | |
| "file": "pages/neural-thickets-repro/page.md", | |
| "children": [] | |
| } | |
| ] | |
| }, | |
| "agent_view_tokens": 8341, | |
| "revision": "1784147252924102000" | |
| } |