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Paper Citation Record · LEDGER

Efficient Tuning and Inference for Large Language Models on Textual Graphs

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 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 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:18:17.879790Z

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 4df42747-8387-4324-9ee9-c3836ef79e31 · inbound

Each Graph is a New Language: Graph Learning with LLMs cites this paper.

Each Graph is a New Language: Graph Learning with LLMs Efficient Tuning and Inference for Large Language Models on Textual Graphs

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T18:18:17.879790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:18:17.879790Z digest=sha256:d6ebb7e19228e28f47fec34f5c88e764d01ba6ca477f8cab05790974c899f719

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-22T21:26:35.707533Z digest=sha256:c65e0a193aa11b82101262a0b6532229487d69459ea5ff043a3c25bb6257eec2

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=sha256:32bb3e51ebd7a858c162d53d10ec84a2aedb6a89f3cf3859366b52d852134781

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T08:45:51.992431Z digest=sha256:aee807a0ab382a32eb9076ded42980d4f514c26b7b41c8ef4faf9a1582c43088

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-13T04:45:34.957298Z digest=sha256:5f02ba1e9ec1ab1b0f606fd9ac8b0bdf1c3cae81f7c09c1728fe414bbf690b0f

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-27T09:41:14.904868Z digest=sha256:eb74d06b2a3f98f40a1b295f1a6e37df706611fa17606621a0e125329775885a

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-30T06:06:46.108334Z digest=sha256:6c99f360b7380d7e95d71989cbe52b5384ba7e983722a10a0889eb512e181921

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-07-01T06:10:26.634933Z digest=sha256:0e86e19d63536a7c689b5204d595bd906a33caf3e923fc08d16f2566a47254e1

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=sha256:46890b7ba0092ffbd7822383d0964731506b5acecb253ecda53816f430ee423b

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=sha256:24a0af425b988fb223f6bbac9a7457305681c040914399723c28f6da63fb4667