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Paper Citation Record · LEDGER

Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2309.17272.

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

pith.paper-citation-record.v1
2309.17272 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:52:04.880765Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:59:19.035398Z

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 520302b2-edcc-4b9b-92c4-d8379cd4d554 · inbound

Political-LLM: Large Language Models in Political Science cites this paper.

Political-LLM: Large Language Models in Political Science Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 250

Resolution
unresolved
no resolver link, observed 2026-08-11T19:52:04.880765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:52:04.880765Z digest=sha256:5e7c69bbe2d8a6ae97d14967e50e2ed1b1d9360804fa818de51e88714ced3894

Observation 3c944b78-1647-4ff2-bd2f-9e58d71e06ad · inbound

SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution cites this paper.

SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T21:25:58.916728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:25:58.916728Z digest=sha256:d67a3b64461bcb109ac38369726a3c773e1b6194a7b399f5ffd016e6937ad769

Observation 05b2843a-be17-4e07-a091-5aa9935f771a · inbound

HackerRank-ASTRA: Evaluating Correctness & Consistency of Large Language Models on cross-domain multi-file project problems cites this paper.

HackerRank-ASTRA: Evaluating Correctness & Consistency of Large Language Models on cross-domain multi-file project problems Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-09T19:46:23.615149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:46:23.615149Z digest=sha256:8d2ac57b3597726dcbd17ef0be3a16331030562b8a064d299da37245466d958c

Observation 6861a483-2a64-4ca9-8b22-1281f01a01ca · inbound

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset cites this paper.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T13:40:17.057331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:40:17.057331Z digest=sha256:122c9b5b1c6e41e21bdfb18e89b151a3c99b263b1b07aff1d593ae3ab975cbe8

Observation f1d29f0e-ab03-40c0-b6b3-1a21a1efbd18 · inbound

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 290

Resolution
unresolved
no resolver link, observed 2026-08-06T14:13:07.317950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:13:07.317950Z digest=sha256:f12c84b5f09b8fcafb6b6bda5e60d4517b16e120de1157c449d6dd16a0c2d7c8

Observation 7f2695f9-c611-406a-9a57-0ee2880d27d3 · inbound

Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models cites this paper.

Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-18T06:00:57.269361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-18T05:59:00.400429Z digest=sha256:33933bbd3992fdfed177646042d48fbef6fb8ddbfd43df44d0fd93f4fb6328fb

Observation 4f5d8842-4ad4-4c7b-85cf-7f4441bd339f · inbound

In Line with Context: Repository-Level Code Generation via Context Inlining cites this paper.

In Line with Context: Repository-Level Code Generation via Context Inlining Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-16T18:08:12.838343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-16T18:04:56.915339Z digest=sha256:e517fb63e4985c291758a65ac5b27934ad5dacde74ad48cfa42b189008428214

Observation 9d5a022c-da39-4951-80be-8b62d8ea868a · inbound

Self-Consistency from Only Two Samples: CoT-PoT Ensembling for Efficient LLM Reasoning cites this paper.

Self-Consistency from Only Two Samples: CoT-PoT Ensembling for Efficient LLM Reasoning Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:41:01.887041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-10T05:40:25.414166Z digest=sha256:efbb33b243a4fbf6fa1835e8026b1155f31a8511d903d8c056fc39e96a3e4ebb

Observation 11e43c05-2c12-4c2d-b5ec-5463bc01f560 · inbound

XSearch: Explainable Code Search via Concept-to-Code Alignment cites this paper.

XSearch: Explainable Code Search via Concept-to-Code Alignment Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-20T16:33:34.157606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-20T16:31:27.989614Z digest=sha256:191f296e7d1a564d9825413a0ad53500aa9877e3d5110ac532cb092e2a8051a8

Observation e3ad7174-397c-4a40-8da4-6d134e6ce91f · inbound

XSearch: Explainable Code Search via Concept-to-Code Alignment cites this paper.

XSearch: Explainable Code Search via Concept-to-Code Alignment Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:59:19.037933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-04T00:55:50.772103Z digest=sha256:d2b521ee41a225f0cc5f0e504ee9318fa640e8a565193c935341b2c47dbf87cd