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Paper Citation Record · LEDGER

Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2504.05518.

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

pith.paper-citation-record.v1
2504.05518 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:55:42.733135Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T21:28:34.222040Z

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 d2b4b161-032e-41cf-bcc1-dafd47853b90 · inbound

Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training cites this paper.

Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T04:55:42.733135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:55:42.733135Z digest=sha256:7c2372a5d69fe6621e7184ee6af099257ae243b1531cc916854e7a7c31ec5a01

Observation a212de34-1206-4fc2-9f64-fca84f3ac51f · inbound

Evaluating Code Reasoning Abilities of Large Language Models Under Real-World Settings cites this paper.

Evaluating Code Reasoning Abilities of Large Language Models Under Real-World Settings Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:28:34.224511Z

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=2026-05-16T21:23:44.762007Z digest=sha256:5d14500b5aa2fadda3782ae5432028a4dd312f944e67ea398217af38e8eca892

Observation 2ed2c21a-4a49-476b-a39c-91381449f997 · inbound

Diagnosing CFG Interpretation in LLMs cites this paper.

Diagnosing CFG Interpretation in LLMs Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:24:46.747680Z

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=arxiv_source observed=2026-05-10T00:24:09.265532Z digest=sha256:71e79519d906f426ff48a76d804b0199a37874707710a64b5f7373adfe2ea36c