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Paper Citation Record · LEDGER

Small-Bench NLP: Benchmark for small single GPU trained models in Natural Language Processing

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2109.10847.

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

pith.paper-citation-record.v1
2109.10847 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T12:49:19.418548Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T12:49:19.449901Z

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 610cb5a2-fd02-42a8-a137-3623c776bb86 · inbound

DeBERTa: Decoding-enhanced BERT with Disentangled Attention cites this paper.

DeBERTa: Decoding-enhanced BERT with Disentangled Attention Small-Bench NLP: Benchmark for small single GPU trained models in Natural Language Processing

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-13T04:50:53.642537Z

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=2026-05-13T04:50:53.587891Z digest=sha256:1a4fdba2a47ddf4090a48493fc63f4ab8193f66842b64bc2e9b4262beb5c3a15

Observation 8d4839db-9aac-4803-90cc-b06b7db7dedb · inbound

DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing cites this paper.

DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing Small-Bench NLP: Benchmark for small single GPU trained models in Natural Language Processing

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-15T12:49:19.451926Z

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=2026-05-15T12:49:19.418548Z digest=sha256:f6c06316f17c59046d1cc22ac2d6aab534f2b56e4dd5390c80a909fef6913df3