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

Pinned version v1.0 (entry LD06-SL-C07--v1.0) — this page never floats to newer evidence.

This pinned version is also the current version.

Versions:v1.0 · current

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

LD-06 v0.1

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; fixture fixtures/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".