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Paper Citation Record · LEDGER

Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2404.07103.

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

pith.paper-citation-record.v1
2404.07103 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:05:50.733558Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T18:47:16.655497Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

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Pith citing papers

Observation 8b78d2f8-f0d3-4d92-9903-42b43f168d9b · inbound

STEP: Enhancing Video-LLMs' Compositional Reasoning by Spatio-Temporal Graph-guided Self-Training cites this paper.

STEP: Enhancing Video-LLMs' Compositional Reasoning by Spatio-Temporal Graph-guided Self-Training Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 16

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no resolver link, observed 2026-08-12T06:02:33.891781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T06:02:33.891781Z digest=sha256:7b8e0fee12fe311df9083416336258588537cef7e8fad8e244cdc99195d1da33

Observation a1fb0a1f-e8eb-4d9c-af31-3aeb5e7d99ba · inbound

Zero-Shot Prompting Approaches for LLM-based Graphical User Interface Generation cites this paper.

Zero-Shot Prompting Approaches for LLM-based Graphical User Interface Generation Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 31

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no resolver link, observed 2026-08-11T15:07:30.518686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:07:30.518686Z digest=sha256:9b22355ee45d1d49e9b39a1903fb3ae055fe389be5e405e7898cf7a41d020c75

Observation 78ea33b0-6541-487a-aa8f-e0c872228f8d · inbound

HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases cites this paper.

HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:46:47.587390Z digest=sha256:26f0de6c7a53d796fbdcda3d5aa79bb66b839b0fc8b5edeff9428901fc126603

Observation 878a0dae-5f10-4f4a-9912-c90887b74fd5 · inbound

Retrieval-Augmented Generation with Graphs (GraphRAG) cites this paper.

Retrieval-Augmented Generation with Graphs (GraphRAG) Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 186

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verified exact
arxiv_id, observed 2026-05-18T04:33:39.330293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 88f63ec8-2f77-4345-830c-7e8016c496e3 · inbound

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey cites this paper.

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 81

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:15:25.314649Z digest=sha256:deb8cad250de24a8ea89b989b5289b78d82ca6c4cd15a71f70ed5b5ea4313503

Observation 607eefad-d6c5-450b-ab96-1d2d571b4bbd · inbound

Graph RAG-Tool Fusion cites this paper.

Graph RAG-Tool Fusion Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 2

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no resolver link, observed 2026-08-08T13:28:39.799211Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:28:39.799211Z digest=sha256:24e9906d415c0d3ff5b3382cbf333704c35e11ebb0f29b093088dd10c6c91fd1

Observation 80d399f6-c381-4453-b4d5-df33ec6aca09 · inbound

GCoT: Chain-of-Thought Prompt Learning for Graphs cites this paper.

GCoT: Chain-of-Thought Prompt Learning for Graphs Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 18

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source=pdf_text observed=2026-08-08T10:55:16.486332Z digest=sha256:32042935ee8e5dc103e461a5186088004be038241561b14b91f47dcf04d0c6bf

Observation 472b73fb-7845-4b36-b994-8a7dca9be0f6 · inbound

KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG cites this paper.

KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 17

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no resolver link, observed 2026-08-07T22:03:31.127856Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:03:31.127856Z digest=sha256:e40f040e79613b526e810c03dad57551d9213cd994a8054299b0f3e553abee02

Observation e6105f36-0cea-4621-8111-48c860fbd5e7 · inbound

DSADF: Thinking Fast and Slow for Decision Making cites this paper.

DSADF: Thinking Fast and Slow for Decision Making Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 24

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no resolver link, observed 2026-08-15T22:05:50.733558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:05:50.733558Z digest=sha256:6f5c6a2fbf129442afd1ac0b88d2f98cc96273dbf27b68cae6b40238a0b16c69

Observation 7ae8e053-d3cf-4c7d-a614-53c42a35e243 · inbound

Rank, Chunk and Expand: Lineage-Oriented Reasoning for Taxonomy Expansion cites this paper.

Rank, Chunk and Expand: Lineage-Oriented Reasoning for Taxonomy Expansion Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 14

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Unavailable: canonical work link unavailable.

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Observation 8f77929d-6854-47b7-b435-7ac8e415cb8c · inbound

Walk&Retrieve: Simple Yet Effective Zero-shot Retrieval-Augmented Generation via Knowledge Graph Walks cites this paper.

Walk&Retrieve: Simple Yet Effective Zero-shot Retrieval-Augmented Generation via Knowledge Graph Walks Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 21

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no resolver link, observed 2026-08-07T14:58:34.737634Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:58:34.737634Z digest=sha256:2b0cd11290b1c3c8bab939edc206b4fce290c5d84920ca8f6e20f2ab2d074a3d

Observation e45a8ccf-12e5-42c6-95a7-48140c4677eb · inbound

Don't Think Longer, Think Wisely: Optimizing Thinking Dynamics for Large Reasoning Models cites this paper.

Don't Think Longer, Think Wisely: Optimizing Thinking Dynamics for Large Reasoning Models Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 14

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no resolver link, observed 2026-08-07T13:30:20.658858Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:30:20.658858Z digest=sha256:4d9c6a50e45ccfb701b908332c8cd8ad64f6f28471e87718b5802171c75300e8

Observation 25bd15e8-66c3-4d74-853d-9c414bb2aeed · inbound

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG cites this paper.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 19

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source=pdf_text observed=2026-08-07T12:09:54.842400Z digest=sha256:2bacbaf0ccd5dac5620c4b7638b9957d998a98d5f3dd72a0decc81703f9c5f6e

Observation e66e7667-9ad3-455a-8e30-50cffcc77095 · inbound

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering cites this paper.

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 27

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no resolver link, observed 2026-08-07T04:47:37.174141Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:37.174141Z digest=sha256:b06e4ba017c73ab104af98a45a667fdd71cebe820e7313c179b08f91e48093d1

Observation 01e4d8dd-532b-4c51-b697-43c1f4837be4 · inbound

ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs cites this paper.

ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:40:08.808188Z digest=sha256:a274bade51dd8534133f1c2538ec6e54872d7f2f4f95f03489d5d4aaa1181248

Observation 3918d574-c0d3-444c-bfdc-7e517cd51227 · inbound

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning cites this paper.

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 29

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no resolver link, observed 2026-08-15T18:39:18.700039Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:39:18.700039Z digest=sha256:23ec334fe0728f027e02204349ef95d008c4e85df05bf672f6c387eb13ba1502

Observation 4cbae3d5-fb93-468b-878f-4c979fd6f446 · inbound

GraphRunner: A Multi-Stage Framework for Efficient and Accurate Graph-Based Retrieval cites this paper.

GraphRunner: A Multi-Stage Framework for Efficient and Accurate Graph-Based Retrieval Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 14

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no resolver link, observed 2026-08-06T18:16:31.987520Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:16:31.987520Z digest=sha256:c67c72770128f3c225f601540ae17c295518d60a270192fa2a9f5a9f55f5786c

Observation 11481041-1080-495b-a575-976d77157868 · inbound

Multilevel Analysis of Cryptocurrency News using RAG Approach with Fine-Tuned Mistral Large Language Model cites this paper.

Multilevel Analysis of Cryptocurrency News using RAG Approach with Fine-Tuned Mistral Large Language Model Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 21

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no resolver link, observed 2026-08-05T16:50:43.407334Z

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Unavailable: canonical work link unavailable.

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Observation 9b20539e-8548-4812-bf93-bec63bdeeac1 · inbound

GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning cites this paper.

GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 25

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arxiv_id, observed 2026-05-15T18:50:16.969505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T18:47:06.207176Z digest=sha256:e7aadaae18dbf421698cd7f986fc5d446d647b14afd1fda2181914a4b23e278f

Observation f8e23719-3ab5-45af-9f55-3b59cb79ea51 · inbound

AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning cites this paper.

AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 3

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arxiv_id, observed 2026-05-10T23:50:54.445005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation b02a07f2-b51b-49db-8793-fbcc45a39050 · inbound

Correct Prediction, Wrong Steps? Consensus Reasoning Knowledge Graph for Robust Chain-of-Thought Synthesis cites this paper.

Correct Prediction, Wrong Steps? Consensus Reasoning Knowledge Graph for Robust Chain-of-Thought Synthesis Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 3

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arxiv_id, observed 2026-05-10T12:45:23.914545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T12:44:09.739818Z digest=sha256:19fb26946549c0ffeed79b066121190319d7a65ca2435633fbb84847edfcd4f8

Observation 10c07e59-8f2e-4c0d-bfd4-29fb6d05b886 · inbound

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval cites this paper.

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 148

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arxiv_id, observed 2026-05-10T05:56:11.401971Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-10T05:43:04.813867Z digest=sha256:95f7e3d910a61f3d3528db7e029fceb7f0b2e215c434e4229a67ead11eb3e7a9

Observation fbab12d4-f9ba-4097-b5c9-a57b850c8c5f · inbound

Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory cites this paper.

Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 32

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arxiv_id, observed 2026-05-11T15:51:34.953164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-09T19:10:30.849963Z digest=sha256:f92e8b5c73dadec0a1b73c0dbcfd5b26d59b278915156b68169ef91b66557a49

Observation 51c55be5-166f-4717-a099-a1fb091d09f7 · inbound

Clustering as Reasoning: A $k$-Means Interpretation of Chain-of-Thought Graph Learning cites this paper.

Clustering as Reasoning: A $k$-Means Interpretation of Chain-of-Thought Graph Learning Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 7

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arxiv_id, observed 2026-06-30T11:44:38.466299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T11:38:58.623070Z digest=sha256:35d399283d5e313eaf1fffe7188521939b64042d8a5060855b62701a947091d9

Observation 6ad0c18b-4e4c-430f-9af5-c5c44b753730 · inbound

AGE: Adaptive-masking for Graph Embedding in Graph Retrieval-Augmented Generation cites this paper.

AGE: Adaptive-masking for Graph Embedding in Graph Retrieval-Augmented Generation Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 41

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arxiv_id, observed 2026-07-02T18:47:16.657071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-02T18:01:48.915707Z digest=sha256:ea84bd49a07a008fe12639bd04e86fc1d61c1678be8765c0d425f6a261627424

Observation b0024468-1eff-4237-a7aa-f5f9c890d3d6 · inbound

What makes prompts a graph: necessary and sufficient conditions for prompt graph engineering cites this paper.

What makes prompts a graph: necessary and sufficient conditions for prompt graph engineering Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 20

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Unavailable: canonical work link unavailable.

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