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Paper Citation Record · LEDGER

Graph Reasoning with Large Language Models via Pseudo-code Prompting

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.17906.

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

pith.paper-citation-record.v1
2409.17906 v1

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 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:58:20.491060Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0c833677-3d93-4fc4-9b86-0fe831e7a120 · inbound

MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning cites this paper.

MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning Graph Reasoning with Large Language Models via Pseudo-code Prompting

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T13:58:20.491060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:58:20.491060Z digest=sha256:68f6570a323b697f79d38dd329b1b961d343c87f999605d56939f53287b06025

Observation 9f8b528c-e3e8-44ce-bef6-49dc473fd03b · inbound

Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks cites this paper.

Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Graph Reasoning with Large Language Models via Pseudo-code Prompting

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T15:42:44.000717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:42:44.000717Z digest=sha256:4e21eb653fb10ba52fe07b6c9c2ee801709676a27064394acf88d2cd35d3c055

Observation 5fedc170-3157-4e2a-a44f-650168f9e8cb · inbound

Graph Counselor: Adaptive Graph Exploration via Multi-Agent Synergy to Enhance LLM Reasoning cites this paper.

Graph Counselor: Adaptive Graph Exploration via Multi-Agent Synergy to Enhance LLM Reasoning Graph Reasoning with Large Language Models via Pseudo-code Prompting

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T10:56:39.930679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:56:39.930679Z digest=sha256:8b728bb0a4a3e43d0a0b66541459c7521f01cbd25b28e0ca6ed3e44a53b77ddd

Observation ab5fd424-a82b-49e0-a9b5-e435124490b7 · inbound

Multi-agent Self-triage System with Medical Flowcharts cites this paper.

Multi-agent Self-triage System with Medical Flowcharts Graph Reasoning with Large Language Models via Pseudo-code Prompting

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-17T21:55:19.726411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-17T21:53:47.777529Z digest=sha256:73fc9b6d9e4d0da18e23c761bbc133cf2c467a90f5f62d193acbca7f6075ac52

Observation e9be3ff1-5c00-4d3d-ace9-2e299c783264 · inbound

Factual and Edit-Sensitive Graph-to-Sequence Generation via Graph-Aware Adaptive Noising cites this paper.

Factual and Edit-Sensitive Graph-to-Sequence Generation via Graph-Aware Adaptive Noising Graph Reasoning with Large Language Models via Pseudo-code Prompting

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:56:11.469644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T03:52:34.593773Z digest=sha256:1c7beaf6fc660a37372d5e81cf5c7f3e0034d6f4f6cc31d64842c9c2b614e0c3