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Paper Citation Record · LEDGER

When Do LLMs Help With Node Classification? A Comprehensive Analysis

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2502.00829.

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

pith.paper-citation-record.v1
2502.00829 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T13:51:14.141383Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T11:08:03.216419Z

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 c9862f82-4f52-4b79-8e17-fb6c82347f76 · inbound

When Structure Doesn't Help: LLMs Do Not Read Text-Attributed Graphs as Effectively as We Expected cites this paper.

When Structure Doesn't Help: LLMs Do Not Read Text-Attributed Graphs as Effectively as We Expected When Do LLMs Help With Node Classification? A Comprehensive Analysis

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-17T20:20:11.834826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T20:18:14.565936Z digest=sha256:fa26e7592d3a9b34dfd0e8535305096e12daa53e1294fb6e6ea685818c15a0ec

Observation 654da98b-3272-41be-8762-2da4c3ffeb20 · inbound

HopRank: Self-Supervised LLM Preference-Tuning on Graphs for Few-Shot Node Classification cites this paper.

HopRank: Self-Supervised LLM Preference-Tuning on Graphs for Few-Shot Node Classification When Do LLMs Help With Node Classification? A Comprehensive Analysis

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:06:18.705426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T06:04:24.381169Z digest=sha256:5354a22216457b7c01a9e149e59e5ba7d749a7e816856c0d24261a9595ce3dbf

Observation 56c0e332-d129-4717-b67d-2eb3d643e89e · inbound

G2LoRA: Gradient Orthogonal Low-Rank Adaptation Framework for Graph Continual Learning on Text-Attributed Graphs cites this paper.

G2LoRA: Gradient Orthogonal Low-Rank Adaptation Framework for Graph Continual Learning on Text-Attributed Graphs When Do LLMs Help With Node Classification? A Comprehensive Analysis

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:26:17.561987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T15:25:05.566939Z digest=sha256:a1f093454b27a6aedbdaaeab0a062afa0a90ef6f60283d37866c54883e9f78f7

Observation bfc5b639-4eb2-4541-a540-7ef8872bd789 · inbound

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching cites this paper.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching When Do LLMs Help With Node Classification? A Comprehensive Analysis

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T09:07:47.656553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T10:33:02.954683Z digest=sha256:acab5ccbd3b84f1e00da86cb0f020697867ca18f8f5da954880061aa2c2b558b

Observation 465015af-eab2-4007-9e10-b5b61d8c7408 · 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 When Do LLMs Help With Node Classification? A Comprehensive Analysis

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T11:08:03.217877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T09:41:14.904868Z digest=sha256:e5af886cf3d9763e11c2984d52159fe45674559c98409f7e14c585b64573ae71

Observation df68b919-dcc1-4c5f-958f-70144d1b881f · inbound

GLIP: Graph and LLM Joint Pretraining for Graph-Level Tasks cites this paper.

GLIP: Graph and LLM Joint Pretraining for Graph-Level Tasks When Do LLMs Help With Node Classification? A Comprehensive Analysis

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:34:21.264420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T07:33:27.135616Z digest=sha256:25895668ee7402c691952998ad01767e449bdfa9de9d4de5ff366f679222292a

Observation 438d75a9-db51-4e6d-89d6-35bfc02323e2 · inbound

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

UNIT: Unleash Large Language Models Potential for Graph Continual Learning When Do LLMs Help With Node Classification? A Comprehensive Analysis

Reference 32

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:c7e15a0bcd45145d5e57375e2bdc9de62a7bf511ba0a35488452bc421a16d3f9