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Paper Citation Record · LEDGER

Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2004.13138.

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

pith.paper-citation-record.v1
2004.13138 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:40:26.122601Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T00:16:39.372896Z

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 d9e96766-d37c-4e79-8f2e-d63e3e68f39c · inbound

Error correction, authentication, and false acceptance, probabilities for communication over noisy quantum channels: converse upper bounds on the bit transmission rate cites this paper.

Error correction, authentication, and false acceptance, probabilities for communication over noisy quantum channels: converse upper bounds on the bit transmission rate Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T20:40:26.122601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:40:26.122601Z digest=sha256:bdf3517ddd728edcc3d9eeb6324be2b502197f49536af3c7333f9b9a0cc1b6d8

Observation 68d1f187-85be-4b5c-ba0a-85faea5de762 · inbound

Parallel repetition of expanded, and multiplayer, Quantum games: anchoring, optimal values, generalized error bounds, dependency-breaking as symmetry-breaking cites this paper.

Parallel repetition of expanded, and multiplayer, Quantum games: anchoring, optimal values, generalized error bounds, dependency-breaking as symmetry-breaking Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T21:11:44.245994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:11:44.245994Z digest=sha256:7c9e364608fcb987e52fa41cb550db9a0f3d24f5b060ffa665aa43bbdfdf4173

Observation d96ee947-a5cf-4eb9-a8eb-8acc15aa2ea8 · inbound

Probability distributions over CSS codes: two-universality, QKD hashing, collision bounds, security cites this paper.

Probability distributions over CSS codes: two-universality, QKD hashing, collision bounds, security Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T12:59:56.107751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:59:56.107751Z digest=sha256:6c5c54febfb3d449917f0c9110f7ce0e8450763215f5e0c211dcd4f0ff482c58

Observation 01d9ab05-4d44-4d9f-a3b4-e08519b4eb29 · inbound

XOR Games at Full Tilt: The Hardness of Binary Nonlocal Games cites this paper.

XOR Games at Full Tilt: The Hardness of Binary Nonlocal Games Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-07-10T00:16:39.374286Z

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=2026-07-11T11:50:26.030339Z digest=sha256:81cc1a54e4bf6434414abcd737e3ebf3076337341fbc2f9417c01c3e2ea238bc