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Paper Citation Record · LEDGER

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning

As of 10 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2505.15623.

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

pith.paper-citation-record.v1
2505.15623 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:16:04.171790Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

7 of 7 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5850eb5-d7ce-4d39-b47d-2682eaf22035 · outbound

This paper cites Evaluating Mathematical Reasoning Beyond Accuracy.

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning Evaluating Mathematical Reasoning Beyond Accuracy

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:03.607802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:03.607802Z digest=sha256:defa1d2882411b137a274aaca915c9ddabbfd216d6ac68422bf410d4491d0cd0

Observation b927b42e-f9bc-47b5-9783-42130ff1ace1 · outbound

This paper cites Re- flexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024.

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning Re- flexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:16:04.652364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:16:03.663432Z digest=sha256:278e082fa6ba3b4500281b9217c8a45cdbc72bd77d1b775e7199bd0f8b384c64

Observation 6dbe4463-711e-4a51-86f4-f9d111c6c222 · outbound

This paper cites Large Language Models Cannot Self-Correct Reasoning Yet.

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning Large Language Models Cannot Self-Correct Reasoning Yet

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:03.733510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:03.733510Z digest=sha256:1ebb26613b71e69435e14be5676a536843b5620096746cb8285c8cdd64b8ae9e

Observation a58320bf-2d93-4227-abbf-f42fedf6c163 · outbound

This paper cites When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs.

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:03.807732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:03.807732Z digest=sha256:8b21f376aba456a0aa8192112cc4abcf12e03979b8f632e3b8c4c792b0922c4f

Observation 49a6595a-d6c5-4a78-a503-299cee9c4903 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:03.912097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:03.912097Z digest=sha256:8c9ef1196774c8cf1e235e92324611e741bb488fa2b9d0e43bff8368fdc9159e

Observation 5298d28f-64eb-443d-b2e1-d29ea60e084c · outbound

This paper cites Measuring mathematical problem solving with the math dataset.

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning Measuring mathematical problem solving with the math dataset

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:04.049511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:04.049511Z digest=sha256:b165e3913a050065c1219e9863e4b97df2b62971a96f35693bcf8583efb15cdb

Observation 6a650dde-a334-427f-8f12-d01a3d73ce7e · outbound

This paper cites MathBERT: A Pre-Trained Model for Mathematical Formula Understanding, 2021.

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning MathBERT: A Pre-Trained Model for Mathematical Formula Understanding, 2021

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:16:04.468838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:16:04.171790Z digest=sha256:6c7d6111ba785801ad7a0991283c3550f5c0f3905c11917f78fb9d90b6f8c8d9

Pith citing papers

No inbound Pith citation observations are available.