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Paper Citation Record · LEDGER

X-lifecycle Learning for Cloud Incident Management using LLMs

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.03662.

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

pith.paper-citation-record.v1
2404.03662 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:11:57.531189Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:25:59.398268Z

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 9cc5e6ec-5911-413a-b752-61f2371e6ef4 · inbound

Intent-based System Design and Operation cites this paper.

Intent-based System Design and Operation X-lifecycle Learning for Cloud Incident Management using LLMs

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-08T17:11:57.531189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:11:57.531189Z digest=sha256:35df918a85d1b7712ad43f7c86fb1556af974715158fc9901ad7e3ad1f2d41e7

Observation 99d73c9b-1549-44c8-b813-e4ad32dfd765 · inbound

E2E-REME: Towards End-to-End Microservices Auto-Remediation via Experience-Simulation Reinforcement Fine-Tuning cites this paper.

E2E-REME: Towards End-to-End Microservices Auto-Remediation via Experience-Simulation Reinforcement Fine-Tuning X-lifecycle Learning for Cloud Incident Management using LLMs

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:25:59.406027Z

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=2026-05-10T15:31:09.600785Z digest=sha256:ebd05e661fb87aa43ecc5c5eae967640ca647b8fd7bdd037741bf416b4719ae8