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Paper Citation Record · LEDGER

AC-DC: Adaptive Ensemble Classification for Network Traffic Identification

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.11718.

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

pith.paper-citation-record.v1
2302.11718 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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:37:58.670799Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:45:22.719337Z

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 637b1f50-e3b2-4da3-aceb-87667da1560a · inbound

Cruise Control: Dynamic Model Selection for ML-Based Network Traffic Analysis cites this paper.

Cruise Control: Dynamic Model Selection for ML-Based Network Traffic Analysis AC-DC: Adaptive Ensemble Classification for Network Traffic Identification

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-11T11:37:58.670799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:37:58.670799Z digest=sha256:1595af0a09d805ef9baf773b20f11bbdbcc8ce4c04f11daf0cb538e8ac3bdc7d

Observation bea22191-251b-48c0-82ba-cc43a86cf898 · inbound

SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate cites this paper.

SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate AC-DC: Adaptive Ensemble Classification for Network Traffic Identification

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:45:22.782341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:18.370037Z digest=sha256:0a67d88ec9d33079901236802780691ed32504886986bfa9eff9f4215c2c377a