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Paper Citation Record · LEDGER

Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2404.14963.

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

pith.paper-citation-record.v1
2404.14963 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:24:50.840520Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:47:25.855113Z

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 32bcaa5c-0895-47bd-ba0c-c1ec1d526e2a · inbound

DataComp-LM: In search of the next generation of training sets for language models cites this paper.

DataComp-LM: In search of the next generation of training sets for language models Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 219

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:58:17.376433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T22:58:16.523267Z digest=sha256:a0702d54865a09501781cb3ce2dc3142031becac53ff77040a468f86bec1b029

Observation 3420d96c-d2ef-4ba2-8100-5139a36d6b13 · inbound

Resolving Knowledge Conflicts in Domain-specific Data Selection: A Case Study on Medical Instruction-tuning cites this paper.

Resolving Knowledge Conflicts in Domain-specific Data Selection: A Case Study on Medical Instruction-tuning Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T13:24:50.840520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:24:50.840520Z digest=sha256:0bed0bf04d19ae2086ff8ae35c7f48048ccb42e1c040d13133d3a1762b9fb3a3

Observation df1099cd-a899-4471-9e7e-b93e71de27c0 · inbound

Revisiting Overthinking in Long Chain-of-Thought from the Perspective of Self-Doubt cites this paper.

Revisiting Overthinking in Long Chain-of-Thought from the Perspective of Self-Doubt Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T12:49:11.691171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:49:11.691171Z digest=sha256:2a414629981a08cfbe2afc143555690cb1a8bfb75f1b479539b0fcaf0eee5656

Observation dd28f020-592d-4f50-a337-ffa99d744497 · inbound

A Survey on Large Language Models for Mathematical Reasoning cites this paper.

A Survey on Large Language Models for Mathematical Reasoning Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 113

Resolution
unresolved
no resolver link, observed 2026-08-07T05:14:47.608760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:47.608760Z digest=sha256:12e3de1d358eefcfd97b7b3a98f6cb1cf334e051af44b7e0713c1dfaa7a4e9ff

Observation bf3d2dc8-ec3f-4f87-a879-840526c9c941 · inbound

DuaShepherd: Integrating Stepwise Correctness and Potential Rewards for Mathematical Reasoning cites this paper.

DuaShepherd: Integrating Stepwise Correctness and Potential Rewards for Mathematical Reasoning Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T23:35:36.314813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:35:36.314813Z digest=sha256:df9bde55bd80aa90ea3db61d841911ba60e1f9357e80dfb2c5f9d41585cf02b0

Observation a7347745-e66c-4bba-9d84-dc542ece43ea · inbound

Robust Knowledge Editing via Explicit Reasoning Chains for Distractor-Resilient Multi-Hop QA cites this paper.

Robust Knowledge Editing via Explicit Reasoning Chains for Distractor-Resilient Multi-Hop QA Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-05T12:37:47.063326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T12:37:47.063326Z digest=sha256:130eda4f9761da778ca9f0b0f9f10b9767709e2d80d8403baab8a12223141da2

Observation ab469978-3ffd-433b-8226-b96bc3807d16 · inbound

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery cites this paper.

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:47:25.856979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T18:39:44.696961Z digest=sha256:8de25ac4a0f1a371a15911e641448df523e3236ff8426ffdc388634ee2d97018

Observation 85b8aca7-90ed-4794-b701-79f6778060f0 · inbound

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery cites this paper.

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-02T12:05:07.267016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:05:07.267016Z digest=sha256:d7e0ee24a55ea5570d55445981faba05e13508c19f9ceadf48e4d91d853e5d62

Observation a1a67a53-9e59-41b1-ac60-86a35eb639c8 · inbound

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve cites this paper.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.680880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.680880Z digest=sha256:32526abd4911ed73b63221c1d61f6420db5870a40d3b642091bfb6e1854c88ea