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Paper Citation Record · LEDGER

AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2108.05542.

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

pith.paper-citation-record.v1
2108.05542 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:07:17.101094Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T17:05:24.195161Z

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 ebfdee56-9794-4e77-bb9d-9150aae21f0a · inbound

A Time Series is Worth 64 Words: Long-term Forecasting with Transformers cites this paper.

A Time Series is Worth 64 Words: Long-term Forecasting with Transformers AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T19:17:50.735514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T19:17:50.682744Z digest=sha256:9a6344862218fbe45c37fac1a4c03e94f1e5ed582cf75a394e8b1ae88a7f7b73

Observation ffc496d2-4286-4a0b-95b9-0620d40ba717 · inbound

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks cites this paper.

Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:07:17.101094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:07:17.101094Z digest=sha256:c99a523355519ba17aa800be9573ceebd2ae9e18b951282e1c1a2f5144eb77c4

Observation bb66e313-a6fb-417f-9d8a-0f8909539080 · inbound

Brain Network Analysis Based on Fine-tuned Self-supervised Model for Brain Disease Diagnosis cites this paper.

Brain Network Analysis Based on Fine-tuned Self-supervised Model for Brain Disease Diagnosis AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:47.294186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:47.294186Z digest=sha256:357843d37889eb45079fe6329f12fed000834d48e943bdb8157a523d8fc250dd

Observation 3b4f26f5-2fc9-4b3f-babb-3cb84fa055d9 · inbound

Few-shot Learning on AMS Circuits and Its Application to Parasitic Capacitance Prediction cites this paper.

Few-shot Learning on AMS Circuits and Its Application to Parasitic Capacitance Prediction AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T19:08:26.581979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:08:26.581979Z digest=sha256:c279b377203fc756f0d6d971c0726a60b9d6e34c727e7cb65112aec090a70e9d

Observation 98196713-bbf3-4ba7-a1ad-5230991ed614 · inbound

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models cites this paper.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T15:55:33.474366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:55:33.474366Z digest=sha256:08a380dfa8c788e3aa78b663b4b03feef772549d26d57329dc7fb131ceef7eaf

Observation e6eaf4dc-263d-4407-b688-20dd31d51257 · inbound

Human-Centered Supervision for Sentiment Analysis in Telugu: A Systematic Inquiry Beyond Accuracy cites this paper.

Human-Centered Supervision for Sentiment Analysis in Telugu: A Systematic Inquiry Beyond Accuracy AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T00:56:56.239583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T00:55:50.492277Z digest=sha256:d35d7244a6baaa8453f88b47cde4e60fb43b3c16a98008ebaf42007a0c604192

Observation 4cd682ae-1352-45d6-956a-5400cea40706 · inbound

A Simple but Efficient Transformer-Based Physics-Informed Neural Network for Incompressible Navier--Stokes Equations cites this paper.

A Simple but Efficient Transformer-Based Physics-Informed Neural Network for Incompressible Navier--Stokes Equations AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-21T17:05:24.198745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T17:04:21.164340Z digest=sha256:bef496fef81168d8758e4929d1f144276f9dc2469068249cdd8f7a4cbd9d73c0

Observation 32b5c5a2-e2d0-41ff-8c51-1511a2e838ef · inbound

Semantic Homogenization in Italian Popular Music: A Diachronic Analysis cites this paper.

Semantic Homogenization in Italian Popular Music: A Diachronic Analysis AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-11T12:49:21.657332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T12:49:21.657332Z digest=sha256:1b18dbec1b4f05a54f010e984981be4e12a3e58ad37dcb3e8b5df674f112aade