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Paper Citation Record · LEDGER

LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.04124.

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

pith.paper-citation-record.v1
2004.04124 v2

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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:05:48.964077Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T21:46:31.282718Z

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 15822251-5b15-4390-a588-0a8e2ef8f60f · inbound

CURing Large Models: Compression via CUR Decomposition cites this paper.

CURing Large Models: Compression via CUR Decomposition LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-10T21:46:31.288612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T21:46:30.890162Z digest=sha256:236df4178cca9e7525ce4357dffecf3fd463f0c12752175c33601672af3bc854

Observation 27b4b824-7203-4504-8547-4de25b94baca · inbound

TensorSLM: Energy-efficient Embedding Compression of Sub-billion Parameter Language Models on Low-end Devices cites this paper.

TensorSLM: Energy-efficient Embedding Compression of Sub-billion Parameter Language Models on Low-end Devices LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-15T20:05:48.964077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:05:48.964077Z digest=sha256:1bd62a17b6d5db9c3d19d9126c16832f876d06a323ae36454041ee2a2011c464