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Paper Citation Record · LEDGER

Efficient Tuning and Inference for Large Language Models on Textual Graphs

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2401.15569.

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

pith.paper-citation-record.v1
2401.15569 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:44:53.377716Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T11:08:03.190498Z

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 ce160746-7844-4264-940a-3084b93a8321 · inbound

Toward General and Robust LLM-enhanced Text-attributed Graph Learning cites this paper.

Toward General and Robust LLM-enhanced Text-attributed Graph Learning Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:27:08.313722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T21:26:35.707533Z digest=sha256:1d3460630a3d2e213d0e0907ebfeb00f3a48085769b1df2a6121720ed06b9e0d

Observation 7cc3575c-96c3-4198-8cdc-769b4bca6e7e · inbound

Efficient Text-Attributed Graph Learning through Selective Annotation and Graph Alignment cites this paper.

Efficient Text-Attributed Graph Learning through Selective Annotation and Graph Alignment Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-07T05:44:53.377716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:44:53.377716Z digest=sha256:f1942564776192d4ce132e4372be5eac7bd07871cea55530e82236e288a01638

Observation bda9e114-cf5e-421f-9183-a42ba690fe6d · inbound

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach cites this paper.

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-18T08:46:07.729270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T08:45:51.992431Z digest=sha256:bcf349001410608d6140d737fc865db790c5c06adbdb9ca319dff78b96822924

Observation 6baeb5a8-45cb-401d-a15d-4b2b46ac7ee2 · inbound

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs cites this paper.

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-03T00:07:44.908080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:07:44.908080Z digest=sha256:9f32b050604c120ad47c6c19b827cc4550260417884fd4aa0fa2c789c842cfa4

Observation e4c41c77-a037-4e57-97ad-61b742c28116 · inbound

SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory cites this paper.

SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 65

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T04:57:17.734168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T04:45:34.957298Z digest=sha256:07777742f9ff59cdbdb7141a76c12f3ae7d9c251bca3270dfec9200abc065cc8

Observation 577a9452-7bc4-40c0-9f6a-416635b1a9fe · inbound

GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs cites this paper.

GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 51

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T11:08:03.192006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T09:41:14.904868Z digest=sha256:d416731ffdf76b68d10071ce2d23f48e0c2ec791123988de3dd7fe6a1fcca793

Observation 9d41844d-f4bb-479c-a24a-b4d3ac0b535b · inbound

PromptGNN-sim: Deep Fusion and Alignment of GNN and LLMs for Text-Attributed Graph Learning cites this paper.

PromptGNN-sim: Deep Fusion and Alignment of GNN and LLMs for Text-Attributed Graph Learning Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 45

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T08:24:26.841057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T06:06:46.108334Z digest=sha256:2dc5f277ca9a2c0af7a0ed3cd83856d9bff9e7874038dd32bdb14d42c5685657

Observation 4d4ac506-f08d-4e7d-8bca-03394f083095 · inbound

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning cites this paper.

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 177

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T09:45:40.646819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-01T06:10:26.634933Z digest=sha256:b3262a9fca194ac408e71780c94d1b8b40a99010c082145893b4d55a305e23ee

Observation 1e2fa54c-aad2-4ac6-8f34-0103af77b031 · inbound

UNIT: Unleash Large Language Models Potential for Graph Continual Learning cites this paper.

UNIT: Unleash Large Language Models Potential for Graph Continual Learning Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 44

Resolution
unresolved
no resolver link, observed 2026-07-14T13:51:14.141383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T13:51:14.141383Z digest=sha256:df14a1eb3e987fd67100396f0c2f769b93cdf87e18176459f4d105434ea0d9fa

Observation b2035a67-d696-432d-9478-61420cd65b72 · inbound

Attacking Graph Foundation Models Through Their Shared Representation cites this paper.

Attacking Graph Foundation Models Through Their Shared Representation Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-01T15:05:33.357979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T15:05:33.357979Z digest=sha256:92fc2255330aa14b95f6cd584fff931c715e03a1c47b36475c089c942b6a3660

Observation 1a89a488-396c-4adf-b019-6444d0844813 · inbound

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation cites this paper.

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-01T13:29:54.376422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T13:29:54.376422Z digest=sha256:9fba2ae01c8ac06143abe366e91dc368dc1f8f2ddc0fbabe408ab4cd6a927702