Pith. sign in

Paper Citation Record · LEDGER

Rank and run-time aware compression of NLP Applications

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2010.03193.

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

pith.paper-citation-record.v1
2010.03193 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:21:49.206034Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T13:51:04.530867Z

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 c212aafa-538f-4468-9eaf-9078c4199f5a · inbound

SEE: Sememe Entanglement Encoding for Transformer-bases Models Compression cites this paper.

SEE: Sememe Entanglement Encoding for Transformer-bases Models Compression Rank and run-time aware compression of NLP Applications

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T15:21:49.206034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:21:49.206034Z digest=sha256:53895d04b060105873134b2237fcd2955905c1126c40d19108ed93b6abe023d0

Observation 4301e884-0aca-4471-a445-298086f598ea · inbound

HyperFM: An Efficient Hyperspectral Foundation Model with Spectral Grouping cites this paper.

HyperFM: An Efficient Hyperspectral Foundation Model with Spectral Grouping Rank and run-time aware compression of NLP Applications

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:51:04.536947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-09T23:57:09.022872Z digest=sha256:765662d94fcad927dbf244cf69abec27f6281a4f293a31bbaa257097e1ad8c7a