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Paper Citation Record · LEDGER

TF-DDRL: A Transformer-enhanced Distributed DRL Technique for Scheduling IoT Applications in Edge and Cloud Computing Environments

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.14348.

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

pith.paper-citation-record.v1
2410.14348 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:40:32.153856Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e2e4af05-aa77-4de1-8797-22bd2478bf96 · inbound

Deep Reinforcement Learning for Job Scheduling and Resource Management in Cloud Computing: An Algorithm-Level Review cites this paper.

Deep Reinforcement Learning for Job Scheduling and Resource Management in Cloud Computing: An Algorithm-Level Review TF-DDRL: A Transformer-enhanced Distributed DRL Technique for Scheduling IoT Applications in Edge and Cloud Computing Environments

Reference 153

Resolution
unresolved
no resolver link, observed 2026-08-10T22:40:32.153856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:40:32.153856Z digest=sha256:c1e6344c50e241bbaa03d4f4b5829541894fb2373137616e0302c5f89ed54c77

Observation 2833cfcc-9782-47c0-9fd1-cc9c10c81087 · inbound

Resilience Evaluation of Kubernetes in Cloud-Edge Environments via Failure Injection cites this paper.

Resilience Evaluation of Kubernetes in Cloud-Edge Environments via Failure Injection TF-DDRL: A Transformer-enhanced Distributed DRL Technique for Scheduling IoT Applications in Edge and Cloud Computing Environments

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T15:22:21.816145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:22:21.816145Z digest=sha256:3bfe025ee8d35d1ff7872c4b5e127f2844c02cceae9f0f44dc7678a88e67630a

Observation a192e725-6e51-4712-9382-c9e037bf23cc · inbound

Resilience Evaluation of Kubernetes in Cloud-Edge Environments via Failure Injection cites this paper.

Resilience Evaluation of Kubernetes in Cloud-Edge Environments via Failure Injection TF-DDRL: A Transformer-enhanced Distributed DRL Technique for Scheduling IoT Applications in Edge and Cloud Computing Environments

Reference 2024

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T15:22:26.121513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:22:21.952246Z digest=sha256:256f60fffcd223b1c5757b156aeef69492ed74579106dfe756c1e89ed3d54916