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Paper Citation Record · LEDGER

Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.05980.

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

pith.paper-citation-record.v1
2402.05980 v3

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 2026-08-18T06:34:40.430872+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:35:00.113244Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T21:28:34.226481Z

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 e20be222-7a18-4f67-bfa6-b72f5c6677a9 · inbound

Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension Ability cites this paper.

Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension Ability Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T10:18:01.954867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:18:01.954867Z digest=sha256:aa2fdf698200b333e8bffd9e8a21640358cf8c72f92690679fd4613eb08d9073

Observation 4ef59c8e-6000-4023-aa33-ecb88f882212 · inbound

CoCoNUT: Structural Code Understanding does not fall out of a tree cites this paper.

CoCoNUT: Structural Code Understanding does not fall out of a tree Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T13:13:35.298043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T13:13:35.298043Z digest=sha256:a935278489167841ad708cb62b75ceb21114eab21df4d5e6be6fe5c68a8979ed

Observation efee7a58-e2db-4997-82f1-b0bf7fae6368 · inbound

Benchmarking and Revisiting Code Generation Assessment: A Mutation-Based Approach cites this paper.

Benchmarking and Revisiting Code Generation Assessment: A Mutation-Based Approach Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T22:35:00.113244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:35:00.113244Z digest=sha256:1c63df328fa117724ebd819976f8e75f2a35c2e5e2f4b7b2d9f9336d853e93da

Observation c079ae56-1264-4510-b207-d90468049f90 · inbound

Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning cites this paper.

Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T17:22:46.133788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:22:46.133788Z digest=sha256:6d3906e23837d2f89be0b129e19958d7c5f3265d1a0dba668ba669dc3ec102a0

Observation 6aef8c57-06a4-42cc-a96f-bdc2c9420d78 · 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 Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:28:34.228545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-16T21:23:44.762007Z digest=sha256:8dff9d52ddf1d7cb5e68c8c02a355f3ebed052d300a20377be3de104c2a84cf7