{ "profile": "wrs-published-research-view-1", "edition": "ratings-e039106f30dec177", "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS", "entry": { "id": "nasbench301-surrogate-benchmark-2020", "title": "NAS-Bench-301 learned surrogate architecture benchmark", "summary": "Fits predictive surrogate benchmarks using evaluated DARTS-space architectures to simulate searches over a much larger space than exhaustive tabulation can cover.", "boundary": "The approximately 10^18 space is modeled from tens of thousands of evaluated candidates, not exhaustively trained. Surrogate error, sampling bias and training/noise assumptions remain; its predictions are not exact measurements or proof of a search algorithm's real-world ranking. First two authors contribute equally.", "area": "Neural architecture search evaluation", "topic": "Artificial intelligence", "year": 2020, "lane": "HUMAN", "result": "BENCHMARK", "contribution_kind": "EVALUATION_RESOURCE_DESIGN", "package_id": "nasbench301-surrogate-benchmark-2020", "target": { "record_id": "urn:uuid:7a9a9cff-754b-4e65-a0d8-93d206643b98", "version": 1, "content_hash": "sha256:853f5b5d9397ace81bc41fd2ea1f9eb21c7c8da2e6bb94e02959c96402c1e40b" }, "humans": [ "Julien Siems", "Lucas Zimmer", "Arber Zela", "Jovita Lukasik", "Margret Keuper", "Frank Hutter" ], "authors_complete": true, "human_role_note": "Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.", "agents": [], "related": [], "subresults": [], "scientific_assessment": { "source_review": "SOURCE_CURATED", "scientific_review": "NOT_REVIEWED_BY_WRS", "formal_replay": "NOT_RUN", "provider_attestation": "NONE" }, "sources": [ { "id": "ai-oct15-arxiv-2008-09777v1", "title": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } ], "points": "75000", "published_grade": { "id": "nasbench301-surrogate-benchmark-2020", "entry_id": "nasbench301-surrogate-benchmark-2020", "band": "B", "modifier": "+", "target": { "record_id": "urn:uuid:7a9a9cff-754b-4e65-a0d8-93d206643b98", "version": 1, "content_hash": "sha256:853f5b5d9397ace81bc41fd2ea1f9eb21c7c8da2e6bb94e02959c96402c1e40b" }, "what_changed": "Fits predictive surrogate benchmarks using evaluated DARTS-space architectures to simulate searches over a much larger space than exhaustive tabulation can cover.", "scope": "Fits predictive surrogate benchmarks using evaluated DARTS-space architectures to simulate searches over a much larger space than exhaustive tabulation can cover. The approximately 10^18 space is modeled from tens of thousands of evaluated candidates, not exhaustively trained. Surrogate error, sampling bias and training/noise assumptions remain; its predictions are not exact measurements or proof of a search algorithm's real-world ranking. First two authors contribute equally.", "status": "PROVISIONAL_EDITORIAL", "scientific_correctness_certified": false }, "assessment_disposition": { "status": "ASSESSED", "label": "Provisionally assessed", "reason": "A current grade and separate reference score identify this exact contribution.", "target": { "record_id": "urn:uuid:7a9a9cff-754b-4e65-a0d8-93d206643b98", "version": 1, "content_hash": "sha256:853f5b5d9397ace81bc41fd2ea1f9eb21c7c8da2e6bb94e02959c96402c1e40b" }, "edition": "ratings-e039106f30dec177" } }, "version": { "kind": "PUBLIC_RECORD_VIEW", "previous": null, "published_at": "2026-10-16T00:00:00Z", "publisher": { "principal_id": "urn:uuid:80116931-785b-40a2-a24b-9d59db0c7e33", "role": "WRS_EDITORIAL_PUBLICATION" }, "record": { "contributors": [ { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Julien Siems", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Lucas Zimmer", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Arber Zela", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Jovita Lukasik", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Margret Keuper", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Frank Hutter", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } } ], "evidence": [ { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-0", "kind": "source_reference", "source": { "citation": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } } ], "origin": "HUMAN_LEGACY", "record_profile": "wrs-local-research-notes-0.1", "record_type": "research_note", "rrp_version": "0.1", "scope": { "description": "The approximately 10^18 space is modeled from tens of thousands of evaluated candidates, not exhaustively trained. Surrogate error, sampling bias and training/noise assumptions remain; its predictions are not exact measurements or proof of a search algorithm's real-world ranking. First two authors contribute equally.", "domain": "Neural architecture search evaluation" }, "sources": [ { "citation": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1" } ], "statement": "# NAS-Bench-301 learned surrogate architecture benchmark\n\nFits predictive surrogate benchmarks using evaluated DARTS-space architectures to simulate searches over a much larger space than exhaustive tabulation can cover.\n\n## Scientific scope\n\nThe approximately 10^18 space is modeled from tens of thousands of evaluated candidates, not exhaustively trained. Surrogate error, sampling bias and training/noise assumptions remain; its predictions are not exact measurements or proof of a search algorithm's real-world ranking. First two authors contribute equally.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nJulien Siems; Lucas Zimmer; Arber Zela; Jovita Lukasik; Margret Keuper; Frank Hutter\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search](https://arxiv.org/pdf/2008.09777v1)\n", "summary": "Fits predictive surrogate benchmarks using evaluated DARTS-space architectures to simulate searches over a much larger space than exhaustive tabulation can cover.", "title": "NAS-Bench-301 learned surrogate architecture benchmark" }, "record_id": "urn:uuid:7a9a9cff-754b-4e65-a0d8-93d206643b98", "version": 1, "source_ref": { "record_id": "urn:uuid:7a9a9cff-754b-4e65-a0d8-93d206643b98", "version": 1, "content_hash": "sha256:853f5b5d9397ace81bc41fd2ea1f9eb21c7c8da2e6bb94e02959c96402c1e40b" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:e177729cfd4ca84deddd8d69f4e383c902dfdd24df89505ef6bfe47e74a205bc" }, "target": { "record_id": "urn:uuid:7a9a9cff-754b-4e65-a0d8-93d206643b98", "version": 1, "content_hash": "sha256:853f5b5d9397ace81bc41fd2ea1f9eb21c7c8da2e6bb94e02959c96402c1e40b" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "nasbench301-surrogate-benchmark-2020", "entry_id": "nasbench301-surrogate-benchmark-2020", "revision": 1, "title": "NAS-Bench-301 learned surrogate architecture benchmark", "context": "Neural architecture search evaluation", "track": "Evaluation resource design", "band": "B", "modifier": "+", "status": "PROVISIONAL_EDITORIAL", "assessed_on": "2026-10-16", "evidence_cutoff": "2026-10-16", "achievement_state": "SUPPORTED_SCOPED_RESULT", "what_changed": "Fits predictive surrogate benchmarks using evaluated DARTS-space architectures to simulate searches over a much larger space than exhaustive tabulation can cover.", "scope": "Fits predictive surrogate benchmarks using evaluated DARTS-space architectures to simulate searches over a much larger space than exhaustive tabulation can cover. The approximately 10^18 space is modeled from tens of thousands of evaluated candidates, not exhaustively trained. Surrogate error, sampling bias and training/noise assumptions remain; its predictions are not exact measurements or proof of a search algorithm's real-world ranking. First two authors contribute equally.", "evidence_summary": "The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. The approximately 10^18 space is modeled from tens of thousands of evaluated candidates, not exhaustively trained. Surrogate error, sampling bias and training/noise assumptions remain; its predictions are not exact measurements or proof of a search algorithm's real-world ranking. First two authors contribute equally.", "references": [ { "title": "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/pdf/2008.09777v1", "locator": "Original contribution and stated assumptions, evaluation scope and limitations; source-linked assessment, not independent execution or proof certification." } ], "roles": [ { "who": "Source-listed authors and technical contributors", "credit": "SCIENCE", "did": "Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities." } ], "target": { "record_id": "urn:uuid:7a9a9cff-754b-4e65-a0d8-93d206643b98", "version": 1, "content_hash": "sha256:853f5b5d9397ace81bc41fd2ea1f9eb21c7c8da2e6bb94e02959c96402c1e40b" }, "scientific_correctness_certified": false, "independent_expert_calibration": false, "method": "PROPRIETARY", "points": "75000" }, "canonical_agent_submission": false, "scientific_verification_awarded": false, "reader_guide": null, "reading_status": "SOURCE_LINKED_NOTE" }