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Paper Citation Record · LEDGER

A Survey of Multi-Tenant Deep Learning Inference on GPU

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.09040.

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

pith.paper-citation-record.v1
2203.09040 v3

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 2026-08-07T01:02:22.063660Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T02:45:56.099289Z

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 d1864ef3-06a5-4785-8387-34d79e203767 · inbound

THEMIS: Time, Heterogeneity, and Energy Minded Scheduling for Fair Multi-Tenant Use in FPGAs cites this paper.

THEMIS: Time, Heterogeneity, and Energy Minded Scheduling for Fair Multi-Tenant Use in FPGAs A Survey of Multi-Tenant Deep Learning Inference on GPU

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:45:56.101788Z

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=2026-05-24T02:45:48.455887Z digest=sha256:95c841178716d44cf0efb03a4c4dc0a95aed4b18de461638940a7e0785f23428

Observation 11df8dcc-e85f-4b8c-8568-d16fc55a3630 · inbound

Efficient Unified Caching for Accelerating Heterogeneous AI Workloads cites this paper.

Efficient Unified Caching for Accelerating Heterogeneous AI Workloads A Survey of Multi-Tenant Deep Learning Inference on GPU

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-07T01:02:22.063660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:02:22.063660Z digest=sha256:a39af0655e096db9fb61a3eaba5e619ae730429ad628dd7f895b4d393a3c2297

Observation 15aeeabb-c117-4930-8f79-9ec2b3ff13bc · inbound

Strait: Perceiving Priority and Interference in ML Inference Serving cites this paper.

Strait: Perceiving Priority and Interference in ML Inference Serving A Survey of Multi-Tenant Deep Learning Inference on GPU

Reference 108

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:06:29.000055Z

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=2026-05-07T07:50:05.245164Z digest=sha256:f69cfb331f1e0f67202239f9969dd40aa922570abc61031eb55506a80159041a