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Paper Citation Record · LEDGER

DQRM: Deep Quantized Recommendation Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.20046.

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

pith.paper-citation-record.v1
2410.20046 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:29:02.024766Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T05:41:04.564605Z

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 66d67b77-085a-4970-976d-03dcc033847c · inbound

HE-LRM: Encrypted Deep Learning Recommendation Models using Fully Homomorphic Encryption cites this paper.

HE-LRM: Encrypted Deep Learning Recommendation Models using Fully Homomorphic Encryption DQRM: Deep Quantized Recommendation Models

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-06T23:29:02.024766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:29:02.024766Z digest=sha256:ca3df4e6b8b8026f11908b67d1911489267e1f22863b95b862f4441ce2eb8bfa

Observation 7b623c7a-6a2b-4a9f-b556-f9731ac4ff9c · inbound

NestPipe: Large-Scale Recommendation Training on 1,500+ Accelerators via Nested Pipelining cites this paper.

NestPipe: Large-Scale Recommendation Training on 1,500+ Accelerators via Nested Pipelining DQRM: Deep Quantized Recommendation Models

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:41:04.570750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:58:46.821857Z digest=sha256:9d155ddf95dc5cf76b07c085d4e0e227430514ffe3b5b20bb2ef94ec8649ff9b