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Paper Citation Record · LEDGER

Pretraining on the Test Set Is All You Need

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2309.08632.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2309.08632 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:58:02.194748Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-12T03:01:18.700393Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0590d537-9128-49c8-b4e7-a621730fd540 · inbound

Chameleon: Mixed-Modal Early-Fusion Foundation Models cites this paper.

Chameleon: Mixed-Modal Early-Fusion Foundation Models Pretraining on the Test Set Is All You Need

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:03:28.180135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-11T10:03:27.919346Z digest=sha256:6c70e37c8c6d12a036ce1f6b39e927f7d9e42daa8f9fb541fa6237e747922764

Observation 3f54566c-a699-4e30-9607-afe0c6aa060a · inbound

AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledge cites this paper.

AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledge Pretraining on the Test Set Is All You Need

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T12:58:02.194748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:58:02.194748Z digest=sha256:58f051acf5c455a059fa95d39d2b0b1ae6b77fabb63dc22ddbcd871c52380efd

Observation bd0f899a-7db6-4407-834b-1bd67fdfe751 · inbound

Language Models Improve When Pretraining Data Matches Target Tasks cites this paper.

Language Models Improve When Pretraining Data Matches Target Tasks Pretraining on the Test Set Is All You Need

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-06T16:53:13.267905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:53:13.267905Z digest=sha256:3e9dca1f7f1dc09f48514ab62f99c4b9770bc3ed824da0b523093cee6913ccf7

Observation 3cf9e6df-393b-4b02-adde-6800a7912adf · inbound

Pretraining on the Test Set Is No Longer All You Need: A Debate-Driven Approach to QA Benchmarks cites this paper.

Pretraining on the Test Set Is No Longer All You Need: A Debate-Driven Approach to QA Benchmarks Pretraining on the Test Set Is All You Need

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T14:44:09.416573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:44:09.416573Z digest=sha256:17f55a1aa8dd2f85e65923f10431a9570ad1ff84d30e2519629bac55a2d0812b

Observation 6fc3b000-7dd9-4d03-9a3c-bf3d3c62f501 · inbound

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces cites this paper.

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces Pretraining on the Test Set Is All You Need

Reference 74

Resolution
verified exact
arxiv_id, observed 2026-05-12T03:01:18.702387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-12T02:57:15.521594Z digest=sha256:a0fc9da23976927ba2615d19366b30572e1e99ca241b1b7667afa196d40bad76