Paper Citation Record · LEDGER

Graph Representation-based Model Poisoning on Federated Large Language Models

As of 20 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2507.01694.

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

pith.paper-citation-record.v1
2507.01694 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:51:12.475584Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy4
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 958d98e4-3e8f-400b-b01c-97c8abf2313a · outbound

This paper cites Towards federated large language models: Motivations, methods, and future directions,.

Graph Representation-based Model Poisoning on Federated Large Language Models Towards federated large language models: Motivations, methods, and future directions,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:11.321809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cdbcd9b-8d35-4fcf-a0bf-a5a6665b0182 · outbound

This paper cites A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges.

Graph Representation-based Model Poisoning on Federated Large Language Models A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:11.399841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54b92018-1868-4f35-9f6f-f16d4e0cb4d4 · outbound

This paper cites Secure and private over-the-air federated learning: Biased and unbiased aggregation design,.

Graph Representation-based Model Poisoning on Federated Large Language Models Secure and private over-the-air federated learning: Biased and unbiased aggregation design,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:51:12.592948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3a0e8006-2757-46ef-a0ff-6320a3212314 · outbound

This paper cites Fedsecurity: A benchmark for attacks and defenses in federated learning and federated llms,.

Graph Representation-based Model Poisoning on Federated Large Language Models Fedsecurity: A benchmark for attacks and defenses in federated learning and federated llms,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:11.658413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d948631-43be-45e4-bcd2-91e6e205238b · outbound

This paper cites Lever- age variational graph representation for model poisoning on federated learning,.

Graph Representation-based Model Poisoning on Federated Large Language Models Lever- age variational graph representation for model poisoning on federated learning,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:11.829841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32f7b5a3-f021-4e0f-8cad-e829904005ee · outbound

This paper cites Local model poisoning attacks to{Byzantine-Robust}federated learning,.

Graph Representation-based Model Poisoning on Federated Large Language Models Local model poisoning attacks to{Byzantine-Robust}federated learning,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:11.943820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33427783-00a8-4593-b21e-9781a3a5c052 · outbound

This paper cites Sgan-ra: Reconstruction attack for big model in asynchronous federated learning,.

Graph Representation-based Model Poisoning on Federated Large Language Models Sgan-ra: Reconstruction attack for big model in asynchronous federated learning,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:12.082144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2da21b38-2df2-402a-9106-a5daeecc1c6f · outbound

This paper cites Privacy and robustness in federated learning: Attacks and defenses,.

Graph Representation-based Model Poisoning on Federated Large Language Models Privacy and robustness in federated learning: Attacks and defenses,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:12.206414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52bc0a47-051f-4f1b-a326-697f4fc3bc24 · outbound

This paper cites Efficient driving behavior narration and reasoning on edge device using large language models,.

Graph Representation-based Model Poisoning on Federated Large Language Models Efficient driving behavior narration and reasoning on edge device using large language models,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:51:12.555999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 74df8d15-d335-4362-befe-97f04e7027a7 · outbound

This paper cites Sine: Similarity is not enough for mitigating local model poisoning attacks in federated learning,.

Graph Representation-based Model Poisoning on Federated Large Language Models Sine: Similarity is not enough for mitigating local model poisoning attacks in federated learning,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:12.354732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da104b12-270e-452e-a8d5-5b51f47e1a00 · outbound

This paper cites On harnessing semantic communication with natural language processing,.

Graph Representation-based Model Poisoning on Federated Large Language Models On harnessing semantic communication with natural language processing,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:12.464621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b46bba7-694f-4574-abbb-d431647a82a6 · outbound

This paper cites Federated learning for internet of things: A comprehensive survey,.

Graph Representation-based Model Poisoning on Federated Large Language Models Federated learning for internet of things: A comprehensive survey,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:12.467547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6950895-5e79-440c-9055-02b560932cd6 · outbound

This paper cites Exploring visual explanations for defending federated learning against poisoning attacks,.

Graph Representation-based Model Poisoning on Federated Large Language Models Exploring visual explanations for defending federated learning against poisoning attacks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:51:12.528711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 14300f60-f77d-4721-aee5-8bed23c3daab · outbound

This paper cites A comprehensive survey on graph anomaly detection with deep learning,.

Graph Representation-based Model Poisoning on Federated Large Language Models A comprehensive survey on graph anomaly detection with deep learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:51:12.518825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff263069-d353-4eaf-b701-3ddc541d3f12 · outbound

This paper cites Robust aggregation for federated learning,.

Graph Representation-based Model Poisoning on Federated Large Language Models Robust aggregation for federated learning,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T20:51:12.475584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.