Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T15:42:44.037573Z
Paper Citation Record · LEDGER
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks
As of 11 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 2 inbound Pith citation observations for arXiv:2501.13731.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:43:57.462689Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T17:07:12.215404Z
Reference resolution
26 of 26 outbound references displayed
- verified exact0
- verified fuzzy9
- unresolved17
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bddc8d61-5adc-4d41-acb0-acebb3a425f6 · outbound
This paper cites GPT-4 Technical Report.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks GPT-4 Technical Report
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:43.952528Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3290dca6-cd75-440d-b86d-f31f96cb96d5 · outbound
This paper cites Accurate medium-range global weather forecasting with 3d neural networks.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Accurate medium-range global weather forecasting with 3d neural networks
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.506827Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 23df0579-67ee-4e92-bfba-6a2292f487c4 · outbound
This paper cites Graphwiz: An instruction-following language model for graph computational problems.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Graphwiz: An instruction-following language model for graph computational problems
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.497263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 48067590-2ded-4235-83f7-9d402c0aaa16 · outbound
This paper cites A note on two problems in connexion with graphs.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks A note on two problems in connexion with graphs
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.487852Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ca05c465-65e2-4793-9f28-d58622c709ab · outbound
This paper cites Talk like a graph: Encoding graphs for large language models.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Talk like a graph: Encoding graphs for large language models
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.478147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4ac119a2-8c68-48c8-9f78-4097667906de · outbound
This paper cites The Llama 3 Herd of Models.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks The Llama 3 Herd of Models
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:43.970509Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a117883-bbeb-45ba-9efd-597702d4faae · outbound
This paper cites Qwen2.5-Coder Technical Report.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Qwen2.5-Coder Technical Report
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:43.974434Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e70e92e-03f5-414b-b77e-c604ec043045 · outbound
This paper cites Graphteam: Facilitating large language model-based graph analysis via multi-agent collaboration.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Graphteam: Facilitating large language model-based graph analysis via multi-agent collaboration
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:43.978030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 950a6b8e-890d-4465-a941-3e9a104100a9 · outbound
This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:43.981050Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43dcfc53-45c4-46d8-8420-0dbad8405940 · outbound
This paper cites DeepSeek-V3 Technical Report.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks DeepSeek-V3 Technical Report
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:43.984481Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 80cb9a09-7fa2-4238-a0fa-68e0ea454535 · outbound
This paper cites Graphinstruct: Empowering large language models with graph understanding and reasoning capability.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Graphinstruct: Empowering large language models with graph understanding and reasoning capability
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:43.987862Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b0e4c0ac-90e0-478d-a106-212a89a5395c · outbound
This paper cites Direct preference optimization: Your language model is secretly a reward model.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Direct preference optimization: Your language model is secretly a reward model
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.468032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation b89627e1-1f8f-44f8-88d1-bd37d3d98ab6 · outbound
This paper cites Kumar, Emilien Dupont, Francisco Ruiz, Jordan Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, and Alhussein Fawzi.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Kumar, Emilien Dupont, Francisco Ruiz, Jordan Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, and Alhussein Fawzi
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.456796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 73383f33-4b48-494e-8735-b9ea05b03b3b · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:43.997478Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9f8b528c-e3e8-44ce-bef6-49dc473fd03b · outbound
This paper cites Graph Reasoning with Large Language Models via Pseudo-code Prompting.
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.
Observation 5d5ff92f-0d97-47d5-8d60-f1dd1c81034a · outbound
This paper cites GraphArena: Evaluating and Exploring Large Language Models on Graph Computation.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks GraphArena: Evaluating and Exploring Large Language Models on Graph Computation
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:44.003988Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e47218d7-9aeb-4153-ad5a-b549336ce0f9 · outbound
This paper cites Can language models solve graph problems in natural language? In Thirty-seventh Conference on Neural Information Processing Systems , 2023.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Can language models solve graph problems in natural language? In Thirty-seventh Conference on Neural Information Processing Systems , 2023
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.446417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ac6c2cc3-adde-4e2b-a14d-04b69be3c4ee · outbound
This paper cites Loomba, Shichang Zhang, Yizhou Sun, and Wei Wang.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Loomba, Shichang Zhang, Yizhou Sun, and Wei Wang
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.436747Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 8e361826-ec28-497f-bc91-0737cccd451b · outbound
This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:44.013164Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af09d4f2-7ce4-43f9-beec-a18a25717b0c · outbound
This paper cites GraphEval36K: Benchmarking Coding and Reasoning Capabilities of Large Language Models on Graph Datasets.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks GraphEval36K: Benchmarking Coding and Reasoning Capabilities of Large Language Models on Graph Datasets
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:44.016710Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c1cc4ae-3c7c-4bb5-b92b-25437c76d9f6 · outbound
This paper cites InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:44.020736Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ad2bd53-42c1-4a55-9907-fb2cf9ce32be · outbound
This paper cites GCoder: Improving Large Language Model for Generalized Graph Problem Solving.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks GCoder: Improving Large Language Model for Generalized Graph Problem Solving
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:44.024213Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a047c398-4540-431e-8c23-51affcae936e · outbound
This paper cites Debug like a human: A large language model debugger via verifying runtime execution step by step.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks Debug like a human: A large language model debugger via verifying runtime execution step by step
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:42:44.426436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 6ec3d18d-0440-4628-8953-a62489dc0fc2 · outbound
This paper cites JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:44.030701Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fa57caa-7c10-46c2-be16-a0873076e219 · outbound
This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:44.034066Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc4f00de-9e08-47d3-8c37-e4d55c970e9c · outbound
This paper cites write newline.
Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks write newline
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:44.037573Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation 2524e37f-3834-445b-ad3f-2766ed9f426a · inbound
Teaching LLM to Reason: Reinforcement Learning from Algorithmic Problems without Code cites this paper.
Teaching LLM to Reason: Reinforcement Learning from Algorithmic Problems without Code Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:43:57.462689Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8614ef63-779a-47b6-942a-3cc55fd57ac3 · inbound
Are Large Language Models Suitable for Graph Computation? Progress and Prospects cites this paper.
Are Large Language Models Suitable for Graph Computation? Progress and Prospects Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks
Reference 182
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T17:07:12.216872Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.