Paper Citation Record · LEDGER

Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2409.11585.

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

pith.paper-citation-record.v1
2409.11585 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:53:16.668640Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:58:32.317295Z

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 9cb2b352-c193-4bf7-b119-c9ad04234e25 · inbound

Curriculum Guided Reinforcement Learning for Efficient Multi Hop Retrieval Augmented Generation cites this paper.

Curriculum Guided Reinforcement Learning for Efficient Multi Hop Retrieval Augmented Generation Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T14:53:16.668640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8c0e933-d30f-4ea7-9bcc-5ca9cdfa206a · inbound

FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud cites this paper.

FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T13:28:11.824094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23034032-7953-4eea-b210-966652fd6a78 · inbound

CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning cites this paper.

CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:02:18.645579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04c8206a-16d2-4273-b12c-ad4e49030239 · inbound

DeepRAG: Integrating Hierarchical Reasoning and Process Supervision for Biomedical Multi-Hop QA cites this paper.

DeepRAG: Integrating Hierarchical Reasoning and Process Supervision for Biomedical Multi-Hop QA Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:04:42.571754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e3af2fb-3932-4a66-9aaf-00c82dfa3df1 · inbound

Anomaly Detection and Early Warning Mechanism for Intelligent Monitoring Systems in Multi-Cloud Environments Based on LLM cites this paper.

Anomaly Detection and Early Warning Mechanism for Intelligent Monitoring Systems in Multi-Cloud Environments Based on LLM Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T05:38:24.882430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36aabba0-9fe8-4d92-80f9-dbf71b890671 · inbound

An Intelligent Fault Self-Healing Mechanism for Cloud AI Systems via Integration of Large Language Models and Deep Reinforcement Learning cites this paper.

An Intelligent Fault Self-Healing Mechanism for Cloud AI Systems via Integration of Large Language Models and Deep Reinforcement Learning Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:38:33.617858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c11b5150-d20b-4263-ada3-5d52c1690fb5 · inbound

Leveraging Large Language Model for Intelligent Log Processing and Autonomous Debugging in Cloud AI Platforms cites this paper.

Leveraging Large Language Model for Intelligent Log Processing and Autonomous Debugging in Cloud AI Platforms Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:28:51.284744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89dc7806-95a8-45e0-8a95-a0efe08c1c52 · inbound

FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training cites this paper.

FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:31:08.728877Z

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.

Observation e676bf69-afe7-468e-8038-13b7adc521f3 · inbound

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model cites this paper.

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:58:32.319931Z

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.