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Paper Citation Record · LEDGER

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning

As of 15 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2607.19845.

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

pith.paper-citation-record.v1
2607.19845 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T11:35:16.470429Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

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  • unresolved27
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f3f3952f-276e-4c20-90ed-cf0fc16ea1f9 · outbound

This paper cites Language Models are Few-Shot Learners.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Language Models are Few-Shot Learners

Reference 1

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source=pdf_text observed=2026-08-01T11:35:14.220574Z digest=sha256:d7bc7d9612c9fa4394c7888cd371199d597035c6f2e2f6eda21356ed6500f66e

Observation bfaa04a7-bc3f-4451-8012-b6ca38204940 · outbound

This paper cites Analyzing commonsense emergence in few-shot knowledge models.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Analyzing commonsense emergence in few-shot knowledge models

Reference 2

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source=pdf_text observed=2026-08-01T11:35:14.314044Z digest=sha256:1543b704ed2bdc3ff81afbbb313bb20622640f5df5cefc590ee8497e48796dd6

Observation bf07eef2-a4d9-4aee-bafb-3781a84592cd · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 3

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source=pdf_text observed=2026-08-01T11:35:14.377869Z digest=sha256:a20e64108d4e0ed14e55ae623f73bd6654c6a76ed2d05996771d6d3423a3366f

Observation 25012c92-962a-489c-9caf-b165c95d8b60 · outbound

This paper cites Efficient sentence segmentation using syntactic features.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Efficient sentence segmentation using syntactic features

Reference 4

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source=pdf_text observed=2026-08-01T11:35:14.454436Z digest=sha256:2ab067d34d3bf3837ba47000eb2424866b3cbb1b5713b82c69e41568e84d5d0b

Observation 4255cc71-db05-464d-b43f-773fe9b6de92 · outbound

This paper cites COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs

Reference 5

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source=pdf_text observed=2026-08-01T11:35:14.506477Z digest=sha256:d16c0b548863a7528b6711ece0502b6c212db3569d02d1722fd3c1f97b6e333b

Observation baee08e0-2291-42e4-9918-71c8db077b7c · outbound

This paper cites Unifiedqa: Crossing format boundaries with a single qa system.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Unifiedqa: Crossing format boundaries with a single qa system

Reference 6

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source=pdf_text observed=2026-08-01T11:35:14.578412Z digest=sha256:f59a28ebc9585505aac9fc89ec17cac47146e0e36eb46965fec22cd5d0fd0ce4

Observation 929c7677-3edb-4df7-8bdc-835438ce77aa · outbound

This paper cites an unresolved cited work.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Unresolved cited work

Reference 7

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source=pdf_text observed=2026-08-01T11:35:14.681747Z digest=sha256:c358e0c5327ce83c49a89e3661a392a8c3c70f984c4824be455077ad2433926e

Observation 0de6c091-b9db-4b90-b2aa-e5c3634a6553 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Rouge: A package for automatic evaluation of summaries

Reference 8

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source=pdf_text observed=2026-08-01T11:35:14.759373Z digest=sha256:f7fdd45864fdd1e1b4cb029bac01ec4cd14cd4b875e16b1a8256cd557c0b808b

Observation 9f8c8ad7-7a2c-4d7a-afea-5c8621947e41 · outbound

This paper cites Conceptnet: A practical commonsense reasoning toolkit.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Conceptnet: A practical commonsense reasoning toolkit

Reference 9

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source=pdf_text observed=2026-08-01T11:35:14.843840Z digest=sha256:a96799cd8264ff75bc9bdee247c6efc2f9dd6501c723772d6b77c5dd56b1b838

Observation e26586e1-200b-4aab-a14a-2fc32fdb6314 · outbound

This paper cites Unicorn on rainbow: A universal commonsense reasoning model on a new multitask benchmark.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Unicorn on rainbow: A universal commonsense reasoning model on a new multitask benchmark

Reference 10

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source=pdf_text observed=2026-08-01T11:35:14.884377Z digest=sha256:ccfc91d183545940dd56d4268ae34c8c83a4f096fcc8e9f1e3b29fabb4de8420

Observation fc215424-d4a1-4951-af89-074baf1ab85a · outbound

This paper cites Orca: Progressive Learning from Complex Explanation Traces of GPT-4.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Orca: Progressive Learning from Complex Explanation Traces of GPT-4

Reference 11

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source=pdf_text observed=2026-08-01T11:35:14.964984Z digest=sha256:6193805e51e92fc383af05fc4372eb976cc07c4ff0b9744c367e01625dc6e813

Observation 137f3070-f0cf-4dd8-a7e7-c1eba0513528 · outbound

This paper cites Split and rephrase.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Split and rephrase

Reference 12

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source=pdf_text observed=2026-08-01T11:35:15.045490Z digest=sha256:cf5e804c9dff0b5e81fa0a526aa01eb3748b235b06c835936f4ae6adbb7d1893

Observation b7c9b51f-d4e9-42ff-b706-6279a01ba8c3 · outbound

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

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Reference 13

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source=pdf_text observed=2026-08-01T11:35:15.157642Z digest=sha256:281cd1595f22bf94d4f5c5e10dee3948c72f3fc06af615fe5360ce5953fc816c

Observation b958031c-9746-4cae-8e0b-84682170ffae · outbound

This paper cites Smith, and Yejin Choi.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Smith, and Yejin Choi

Reference 14

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source=pdf_text observed=2026-08-01T11:35:15.234302Z digest=sha256:eb8606664f784d61afdb5ad51a3270b9f56cd6c7ac29b62be4d205263b2b6793

Observation 420c1b91-a611-4562-bbcb-81c285de59fd · outbound

This paper cites Conceptnet.Theory and Applications of Natural Language Processing., pages 121–160, 2013.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Conceptnet.Theory and Applications of Natural Language Processing., pages 121–160, 2013

Reference 15

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source=pdf_text observed=2026-08-01T11:35:15.396025Z digest=sha256:888c7ebfe360ee9a5c4ad93fc53926db553e8fc4af0a212a9972ad44d29e430c

Observation 814370bc-3da4-4b64-864b-046f83c6bae2 · outbound

This paper cites UL2: Unifying Language Learning Paradigms.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning UL2: Unifying Language Learning Paradigms

Reference 16

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source=pdf_text observed=2026-08-01T11:35:15.542008Z digest=sha256:d83117d3e3d833a29de133ac97067a842038e2410af5d71d9daa2ddb045aafbf

Observation 855d0d37-9fb5-4e28-a3de-7ca5c7d91296 · outbound

This paper cites Dibert: Dependency-injected bidirectional encoder representations from transformers.TechRxiv / preprint (dependency-injected BERT variants), 2023.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Dibert: Dependency-injected bidirectional encoder representations from transformers.TechRxiv / preprint (dependency-injected BERT variants), 2023

Reference 17

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source=pdf_text observed=2026-08-01T11:35:15.648017Z digest=sha256:0fcea565aecde4e6adebf08f3fc224b35f45c8b4a820c91efd371ba7c996412c

Observation 2a00b5e8-3b1e-42b8-b146-45edfab5fc9f · outbound

This paper cites Kepler: A unified model for knowledge embedding and pre-trained language representation.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Kepler: A unified model for knowledge embedding and pre-trained language representation

Reference 18

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source=pdf_text observed=2026-08-01T11:35:15.726090Z digest=sha256:133b0f9596265724dcf71d96a4c7ee19e895e97672a91f2886ccdc0f65a02f87

Observation 8ff2603d-9154-4b28-8dec-409505ab90aa · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 19

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source=pdf_text observed=2026-08-01T11:35:15.794486Z digest=sha256:f45dd0e2ad11e3fd82ca91d1d40ea69a84577e6386e1e183380754f2d64b0837

Observation e3ffee43-212b-4796-b8bf-29447ae047ca · outbound

This paper cites Rush, and Yoon Kim Zhou.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Rush, and Yoon Kim Zhou

Reference 20

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source=pdf_text observed=2026-08-01T11:35:15.891384Z digest=sha256:3b2062ad6badfc6446ab63394dabb736a270010ccc8730afb6971bc500eb33bd

Observation 3be5e69c-d31f-4480-b90f-35f566ffe03d · outbound

This paper cites Finetuned Language Models Are Zero-Shot Learners.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Finetuned Language Models Are Zero-Shot Learners

Reference 21

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source=pdf_text observed=2026-08-01T11:35:15.964665Z digest=sha256:f7999ceabb0b60241a5656846a4a2672eb3000ac2809bfbbe10e8825045a1f2f

Observation c220c043-e9ae-4212-8ef7-56590c17322d · outbound

This paper cites KG-BERT: BERT for Knowledge Graph Completion.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning KG-BERT: BERT for Knowledge Graph Completion

Reference 22

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source=pdf_text observed=2026-08-01T11:35:16.084016Z digest=sha256:b237717f5fd4f15cf5f4cb9148591acdcbb7047ddab256cd0b5c0e8f2be78642

Observation 6a99286f-2c1f-4f36-bed8-ea932ceb693b · outbound

This paper cites STaR: Bootstrapping Reasoning With Reasoning.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning STaR: Bootstrapping Reasoning With Reasoning

Reference 23

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source=pdf_text observed=2026-08-01T11:35:16.183416Z digest=sha256:e5afce9fcff2a991cb249c5912aa3a178d4ff0a31b782ff3914c8d972714114c

Observation ff3d988c-7041-4535-8e12-987ab9effb71 · outbound

This paper cites Auto evol-instruct: Automatic instruction evolving for large language models.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Auto evol-instruct: Automatic instruction evolving for large language models

Reference 24

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source=pdf_text observed=2026-08-01T11:35:16.257243Z digest=sha256:178ffa1679f201738cbe9c01e3c79f86f3737f1c266c8765b559f362f41b774a

Observation 4512fbce-9b0b-4ef4-9a28-11b82bc5c04f · outbound

This paper cites Limit-bert: Linguistically informed multi-task bert (syntactic / semantic phrase masking).

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Limit-bert: Linguistically informed multi-task bert (syntactic / semantic phrase masking)

Reference 25

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source=pdf_text observed=2026-08-01T11:35:16.396505Z digest=sha256:d4a9c9fe8ae81d9414fd877493d3a8c733232a334cb81f6a554f566cf14b8329

Observation ca9dd7d6-ee93-486a-8e65-333375087ba1 · outbound

This paper cites Syntactic and semantic phrase masking / semantic-role guided masking for pretraining.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Syntactic and semantic phrase masking / semantic-role guided masking for pretraining

Reference 26

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source=pdf_text observed=2026-08-01T11:35:16.470429Z digest=sha256:d757354a153ea08b1f750b0a5474a3374f9df56880611aeed0f02e6a7ce9a925

Observation 183cfc86-4ba1-4b00-b01b-46d06061d41b · outbound

This paper cites an unresolved cited work.

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning Unresolved cited work

Reference 2024

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source=pdf_text observed=2026-08-01T11:35:16.327221Z digest=sha256:4d8851e6683c095b886cc3083612b1a455fc3dc7c2ae88ca4444b4b2d93ca1c1

Pith citing papers

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