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Paper Citation Record · LEDGER

Can LLMs Solve longer Math Word Problems Better?

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.14804.

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

pith.paper-citation-record.v1
2405.14804 v4

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 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:40:39.872020Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:44:59.607033Z

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 23f0feda-a3e9-42b3-95f5-ecf2217b8a83 · inbound

UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models cites this paper.

UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models Can LLMs Solve longer Math Word Problems Better?

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-10T15:40:39.872020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:40:39.872020Z digest=sha256:904e0085e569156501f77c4df5fcb42bf6027b9e4102394b384d69b7d6050ae1

Observation 7f188138-15eb-44d4-a37e-4245dc88973f · inbound

UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models cites this paper.

UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models Can LLMs Solve longer Math Word Problems Better?

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-09T19:27:46.886984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T19:27:46.886984Z digest=sha256:5210b9e1e222d04b6a2f9b88e74c5115a2d5aeef6c2c4ee49b522bde149018e1

Observation 1ee74c80-f7ec-4123-a69f-08d92a139756 · inbound

Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification cites this paper.

Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification Can LLMs Solve longer Math Word Problems Better?

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:44:59.609963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T10:44:59.473658Z digest=sha256:ec267d29a9fb7eea84f13d72e4b2e88fed48979302b078521b759d6e532ab352

Observation 4ac5293f-9bc9-4bd1-a315-f4521e5e57de · inbound

HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs cites this paper.

HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs Can LLMs Solve longer Math Word Problems Better?

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-03T20:43:41.363870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:43:41.363870Z digest=sha256:131878ce2df90ec82725dd8819dbc83520e343e9941b2ad2977e903f4ed5a7bc

Observation 28dad95c-580c-42f8-b430-4b9794e52db8 · inbound

KNIGHT: Knowledge Graph-Driven Multiple-Choice Question Generation with Adaptive Hardness Calibration cites this paper.

KNIGHT: Knowledge Graph-Driven Multiple-Choice Question Generation with Adaptive Hardness Calibration Can LLMs Solve longer Math Word Problems Better?

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-02T21:28:04.103263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:28:04.103263Z digest=sha256:6732530c94bb90d9d1a5dfcff75fb6f1905ea516f2074fe27f25b98772f2dcde