Paper Citation Record · LEDGER

SpanBERT: Improving Pre-training by Representing and Predicting Spans

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:1907.10529.

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

pith.paper-citation-record.v1
1907.10529 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:31:52.216952Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:06:20.155007Z

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 a0ca66fe-ea1f-4119-a519-3abbb8b02c74 · inbound

RoBERTa: A Robustly Optimized BERT Pretraining Approach cites this paper.

RoBERTa: A Robustly Optimized BERT Pretraining Approach SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T04:47:44.471482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cbe37ed2-4c6e-457f-b06f-8b114db5ebc3 · inbound

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism cites this paper.

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T18:34:44.844288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7b8c01b3-3773-4ba2-a8b8-bda919905e0f · inbound

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations cites this paper.

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:26:58.106271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ae94d6f6-95a6-4c65-9338-b09d49e1de76 · inbound

HuggingFace's Transformers: State-of-the-art Natural Language Processing cites this paper.

HuggingFace's Transformers: State-of-the-art Natural Language Processing SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 158

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:53:59.704523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 430b9fb1-7549-44a2-8769-f8771c58fc4f · inbound

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer cites this paper.

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:37:55.670820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 42d0e3b1-869a-4c90-8ca2-a3040099665b · inbound

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension cites this paper.

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-13T00:14:58.192732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1d583409-88ae-4b2d-bcac-c99bbb2b0d65 · inbound

REALM: Retrieval-Augmented Language Model Pre-Training cites this paper.

REALM: Retrieval-Augmented Language Model Pre-Training SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T09:59:16.190100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f7341c57-118d-43e9-8a38-7c62b45c2aaa · inbound

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators cites this paper.

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-16T10:26:47.622756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a5347c99-5f8e-4aa2-8ce8-f948386f269c · inbound

Exploring Long-Term Prediction of Type 2 Diabetes Microvascular Complications cites this paper.

Exploring Long-Term Prediction of Type 2 Diabetes Microvascular Complications SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T04:31:52.216952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 944e1e30-be0f-42b7-86e2-d928a92ab48d · inbound

Making FETCH! Happen: Finding Emergent Dog Whistles Through Common Habitats cites this paper.

Making FETCH! Happen: Finding Emergent Dog Whistles Through Common Habitats SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T14:22:37.372310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bebc808-59c2-4280-8177-603321b17fa1 · inbound

Structure-Aware Fill-in-the-Middle Pretraining for Code cites this paper.

Structure-Aware Fill-in-the-Middle Pretraining for Code SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T12:14:22.318226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85d5bbcc-9580-481b-8dde-c40165ad7543 · inbound

Masked Diffusion Language Models with Frequency-Informed Training cites this paper.

Masked Diffusion Language Models with Frequency-Informed Training SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T05:46:28.123379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c4c862b-c822-4273-909d-e0d0097894d6 · inbound

PortBERT: Navigating the Depths of Portuguese Language Models cites this paper.

PortBERT: Navigating the Depths of Portuguese Language Models SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:06:20.156895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.