Claim LD06-SL-C07 (v1.0)
On GSM1k, a newly written set of grade-school maths problems built to mirror GSM8K, some model families showed accuracy drops of up to 8% against GSM8K, consistent with partial memorization, but many models, especially frontier ones, showed minimal signs of overfitting.
Provenance and status
- Claim type
- ESTIMATE (as printed: “ESTIMATE”)
- Publication status
- ELIGIBLE (INSTITUTIONAL_POSITION) (as printed: “ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER”)
- Verification state
- CONTENT_VERIFIED_PRIMARY (ABSTRACT_ONLY) (as printed: “CONTENT VERIFIED ABSTRACT”; verified by: UNKNOWN)
- Does not license
- A general contamination rate; conclusions for other benchmarks
- Source (field 6, as printed)
- Zhang, Da, Lee, Robinson, Wu, Song et al., “A Careful Examination of Large Language Model Performance on Grade School Arithmetic,” NeurIPS 2024 Datasets and Benchmarks Track, arXiv:2405.00332
- Source type (field 7)
- PEER_REVIEWED_CONFERENCE_PAPER (as printed: “Peer-reviewed conference paper”)
- Institutional position
- Commercial data and evaluation vendor (Scale AI)
- Maturity (claim evidence / publication maturity)
- EMERGING (as printed: “EMERGING”)
- Recorded date
- 2026-10-15
- Currentness / correction
- This is the current version. No correction or concern relation is recorded on its Sources.
Version
Current version v1.0, resolved through the explicit current pointer CLAIM--LD06-SL-C07.
Pinned Sources (field 6, version-specific)
- “Zhang, Da, Lee, Robinson, Wu, Song et al., “A Careful Examination of Large Language Model Performance on Grade School Arithmetic,” NeurIPS 2024 Datasets and Benchmarks Track, arXiv:2405.00332” → SRC-SL-ZHANG-ET-AL-GSM1K-ARXIV-2405-00332--v1.0 — Zhang, Da, Lee, Robinson, Wu, Song et al., “A Careful Examination of Large Language Model Performance on Grade School Arithmetic,” NeurIPS 2024 Datasets and Benchmarks Track, arXiv:2405.00332; class PEER_REVIEWED_CONFERENCE_PAPER (explicit public provenance pin)
All 25 canonical Claim fields (raw values and normalized values)
| # | Canonical field | Canonical value (verbatim) | Normalized (Claim Value Vocabulary v1.0.2) |
|---|---|---|---|
| 1 | CLAIM ID | LD06-SL-C07 | — |
| 2 | PUBLIC-FACING CLAIM | On GSM1k, a newly written set of grade-school maths problems built to mirror GSM8K, some model families showed accuracy drops of up to 8% against GSM8K, consistent with partial memorization, but many models, especially frontier ones, showed minimal signs of overfitting. | — |
| 3 | CLAIM TYPE | ESTIMATE | base_types: ESTIMATE |
| 4 | RESEARCH STRAND | A — Benchmark validity and measurement | — |
| 5 | MATURITY | EMERGING | states: EMERGING |
| 6 | SOURCE | Zhang, Da, Lee, Robinson, Wu, Song et al., “A Careful Examination of Large Language Model Performance on Grade School Arithmetic,” NeurIPS 2024 Datasets and Benchmarks Track, arXiv:2405.00332 | source_ids: SRC-SL-ZHANG-ET-AL-GSM1K-ARXIV-2405-00332 |
| 7 | SOURCE TYPE | Peer-reviewed conference paper | classes: PEER_REVIEWED_CONFERENCE_PAPER |
| 8 | INSTITUTIONAL POSITION | Commercial data and evaluation vendor (Scale AI) | — |
| 9 | SCOPE | Elementary mathematical reasoning | — |
| 10 | DESIGN | New held-out benchmark matched to GSM8K on difficulty and form | — |
| 11 | SAMPLE / DATASET | GSM1k problems (the count is not given in the abstract) | — |
| 12 | MODEL / TOOL / VERSION | Leading open and closed models as of 2024 | — |
| 13 | COMPARATOR | The same models on GSM8K | — |
| 14 | MAIN RESULT | Accuracy drops of up to 8%; Spearman’s r² = 0.36 between a model’s probability of generating GSM8K items and its GSM8K–GSM1k gap; minimal overfitting for many frontier models | — |
| 15 | INFERENTIAL TARGET | Contamination as a cause of inflated benchmark scores | — |
| 16 | DOES NOT LICENSE | A general contamination rate; conclusions for other benchmarks | — |
| 17 | VERIFICATION STATE | CONTENT VERIFIED ABSTRACT | state: CONTENT_VERIFIED_PRIMARY · qualifiers: ABSTRACT_ONLY · verified_by: UNKNOWN |
| 18 | LIMITATIONS | Read in abstract only; one task family; the authors’ company sells evaluation data | — |
| 19 | CONTRADICTORY / SUPPORTING SOURCES | Counterweight to blanket contamination claims; compare LD06-SL-C03 on label errors | — |
| 20 | GEOGRAPHY / LANGUAGE | Not checked / English | — |
| 21 | DISTRIBUTIONAL LEDGER | Not analysed in this claim | — |
| 22 | R01 / FIELD-MAP LINKS | LD-06, D4b | — |
| 23 | WHAT WOULD CHANGE THIS CLAIM? | Held-out replications for other benchmarks and newer models | — |
| 24 | PUBLICATION STATUS | ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER | state: ELIGIBLE · qualifiers: INSTITUTIONAL_POSITION |
| 25 | RECORDED DATE | 2026-10-15 | — |
Field 22 references resolved against Field Map v0.2: LD-06 (LIVING_DEBATE); D4b (SUB_AREA)
Cited by Living Debate versions
Research-of-record provenance
Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 9b061dc9288dd050d4ba1194c8d1ca5a54e3d44ff0098b76b195ec9b4e98f6e7.
Repository-authored inputs (not Drive exports)
- SocioLens claim — LD06-SL-C07 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-15; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-06 debate; a new Claim, first version, written from the project's LD-06 source notes, checked against full texts or official abstracts. Block “ENTRY 07 — LD06-SL-C07” SHA-256
81f61be4358d8288f71a9e0cbde18f46e67ea20c927d57c947721fbc1e9441a7; fixturefixtures/authored/claims/LD06-SL-C07--v1.0.
Builder decisions (not Drive data)
- VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD06-SL-C07 v1.0); the first version of a new Claim of the LD-06 debate
- CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD06-SL-C07 v1.0" (Project Lead (Claude, AI), 2026-10-15); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-06 debate; a new Claim, first version, written from the project's LD-06 source notes, checked against full texts or official abstracts
- FIELD_6_SOURCE_REFERENCE = SRC-SL-ZHANG-ET-AL-GSM1K-ARXIV-2405-00332--v1.0 — basis: field 6 of ENTRY 07 — LD06-SL-C07 cites "Zhang, Da, Lee, Robinson, Wu, Song et al., “A Careful Examination of Large Language Model Performance on Grade School Arithmetic,” NeurIPS 2024 Datasets and Benchmarks Track, arXiv:2405.00332"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
- SOURCE_PROVENANCE_PIN = SRC-SL-ZHANG-ET-AL-GSM1K-ARXIV-2405-00332--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Zhang, Da, Lee, Robinson, Wu, Song et al., “A Careful Examination of Large Language Model Performance on Grade School Arithmetic,” NeurIPS 2024 Datasets and Benchmarks Track, arXiv:2405.00332".