Paper Citation Record · LEDGER

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding

As of 16 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 3 inbound Pith citation observations for arXiv:1908.04577.

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

pith.paper-citation-record.v1
1908.04577 v3

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:42:20.427601Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:38:41.735094Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T08:06:06.195097Z

Reference resolution

35 of 35 outbound references displayed

verified exact2
verified fuzzy12
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bea6b3ad-1e7f-4b6a-b413-540ece6daba9 · outbound

This paper cites The ﬁfth pascal recognizing textual entailment challenge.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding The ﬁfth pascal recognizing textual entailment challenge

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.830797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f8ecdf63-2514-461c-8d7a-a622d15f7f8b · outbound

This paper cites A bottom-up approach to sentence ordering for multi-document summarization.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding A bottom-up approach to sentence ordering for multi-document summarization

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.818820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 64755cd8-e80f-4072-90b8-7f6343c3eecc · outbound

This paper cites A large annotated corpus for learning natural language inference.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding A large annotated corpus for learning natural language inference

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.306521Z

Source-reported events for the cited work

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Observation 482713ee-696d-44b6-a5b9-de79540f6eac · outbound

This paper cites SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.310917Z

Source-reported events for the cited work

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Observation 93ff61b1-dac3-4a29-a73f-07863c4c33ec · outbound

This paper cites Neural Sentence Ordering.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Neural Sentence Ordering

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.315484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6aacfbf-e12c-42f0-b0c0-c68a17c78809 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.319452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 823d969e-0577-43b5-85c6-f98b19a7e702 · outbound

This paper cites Automatically constructing a corpus of sentential paraphrases.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Automatically constructing a corpus of sentential paraphrases

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.323755Z

Source-reported events for the cited work

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Observation 49f2c672-9c1b-47c6-b7fc-d1f65b077a6b · outbound

This paper cites Finding structure in time.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Finding structure in time

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.327410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dd7c18f-f818-47ef-96cf-be85844a9356 · outbound

This paper cites A Comparison of Neural Models for Word Ordering.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding A Comparison of Neural Models for Word Ordering

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-14T13:42:20.613789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1f7b813e-e2c0-4c10-a16d-7906e6e418ad · outbound

This paper cites Gaussian Error Linear Units (GELUs).

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Gaussian Error Linear Units (GELUs)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.335823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69156bbe-85f9-46f0-9de6-a8c666727396 · outbound

This paper cites Long short-term memory.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Long short-term memory

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.339741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a0c267a-909b-4654-99e0-ada48203b61e · outbound

This paper cites SpanBERT: Improving Pre-training by Representing and Predicting Spans.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding SpanBERT: Improving Pre-training by Representing and Predicting Spans

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.343418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17bbd402-c6b3-4449-9f28-93deffce6a65 · outbound

This paper cites The winograd schema challenge.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding The winograd schema challenge

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.788333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 59dc5ab3-1424-489f-8cc7-1ffbf8c86d7f · outbound

This paper cites Multi-Task Deep Neural Networks for Natural Language Understanding.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.351096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48b3c4aa-e5c5-4376-9009-350b33d16acc · outbound

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

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.354787Z

Source-reported events for the cited work

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Observation 6fe34c44-28eb-45e4-8448-b79f666655a0 · outbound

This paper cites Learned in translation: Contextualized word vectors.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Learned in translation: Contextualized word vectors

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.777652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c4dbae72-9114-43e0-9540-216ebe99fc03 · outbound

This paper cites Recurrent neural network based language model.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Recurrent neural network based language model

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.764757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a6a1dfbd-a233-4bbe-9256-a6760d3f2779 · outbound

This paper cites Deep contextualized word representations.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Deep contextualized word representations

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.365475Z

Source-reported events for the cited work

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Observation fa910d7c-e0af-40c3-adf9-26ace9f9afd4 · outbound

This paper cites Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.369209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 937ad893-81a3-4d16-a1c4-ede075f5e8a7 · outbound

This paper cites Improving language under- standing by generative pre-training.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Improving language under- standing by generative pre-training

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.753104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 76502a54-4a9d-46eb-bad0-6c4d2109d415 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.377372Z

Source-reported events for the cited work

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Observation eb2a8944-3250-457d-9dbd-eb97cc8cd601 · outbound

This paper cites Snorkel: Rapid training data creation with weak supervision.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Snorkel: Rapid training data creation with weak supervision

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.741156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 82361db7-c0ca-4851-bca8-96fd3781eecc · outbound

This paper cites Building applied natural language generation systems.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Building applied natural language generation systems

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.728990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f9416b5c-fb82-48e5-8750-30cd46ded4b8 · outbound

This paper cites Word Ordering Without Syntax.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Word Ordering Without Syntax

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-14T13:42:20.523860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 07def491-e731-44e4-8177-50e97d41a4dd · outbound

This paper cites Recursive deep models for semantic compositionality over a sentiment treebank.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Recursive deep models for semantic compositionality over a sentiment treebank

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.716400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b32913f5-e388-4d0e-9cdf-ef83b7be7903 · outbound

This paper cites Attention is all you need.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Attention is all you need

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.395279Z

Source-reported events for the cited work

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Observation 49268ad8-79ff-4979-9df5-9de1cc7957be · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.398817Z

Source-reported events for the cited work

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Observation 6d67b1f7-5ba4-4885-8734-c47f26d2f32b · outbound

This paper cites Neural Network Acceptability Judgments.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Neural Network Acceptability Judgments

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.402688Z

Source-reported events for the cited work

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Observation 712f05a1-31dd-4ce2-a492-20f71f669158 · outbound

This paper cites A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.406742Z

Source-reported events for the cited work

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Observation 5eae3dd0-1539-4c84-bd71-b8810b565770 · outbound

This paper cites Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.410370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a46087f4-d103-41d3-9d5e-252cc99f6f3e · outbound

This paper cites Enhancing pre-trained language representations with rich knowledge for machine reading comprehension.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Enhancing pre-trained language representations with rich knowledge for machine reading comprehension

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.696005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b71e9937-6258-4aa1-882a-747646ee95bb · outbound

This paper cites XLNet: Generalized Autoregressive Pretraining for Language Understanding.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding XLNet: Generalized Autoregressive Pretraining for Language Understanding

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.417154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a69984a-788b-4316-93e8-dca8370cb259 · outbound

This paper cites QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-14T13:42:20.420809Z

Source-reported events for the cited work

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Observation 4a103c29-03d7-4498-ac20-bae922130934 · outbound

This paper cites Discriminative syntax-based word ordering for text generation.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Discriminative syntax-based word ordering for text generation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.684088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c28b762a-f7f3-4868-bb0f-2ce47f0604a4 · outbound

This paper cites Aligning books and movies: Towards story-like visual explanations by watching movies and reading books.

StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Aligning books and movies: Towards story-like visual explanations by watching movies and reading books

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:20.672220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 6dcf605b-d1ea-4ff6-94d8-338b6c96991c · inbound

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

DeBERTa: Decoding-enhanced BERT with Disentangled Attention StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T04:50:53.675100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 333908a3-a03c-40c8-b0e9-5d4422190e91 · inbound

Can bidirectional encoder become the ultimate winner for downstream applications of foundation models? cites this paper.

Can bidirectional encoder become the ultimate winner for downstream applications of foundation models? StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T11:38:41.735094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13a74964-6292-4fdd-aebe-8c075ba61a1e · inbound

CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis cites this paper.

CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T08:06:06.200840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.