Paper Citation Record · LEDGER

Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2003.07082.

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

pith.paper-citation-record.v1
2003.07082 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:50:52.330848Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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 fdb0146f-b305-44df-8301-19bf05e65c3a · inbound

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

HuggingFace's Transformers: State-of-the-art Natural Language Processing Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 177

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:53:59.813577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation daf5fb8b-0cc1-43a4-bb2f-fe0fbe45f0b5 · inbound

Mechanistic Decomposition of Sentence Representations cites this paper.

Mechanistic Decomposition of Sentence Representations Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:52.330848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 213d288c-62ad-464c-a708-530c35a4b8d7 · inbound

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language cites this paper.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:41.693007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00d34718-879b-4a9b-b75d-12643fe64e54 · inbound

Verified Language Processing with Hybrid Explainability: A Technical Report cites this paper.

Verified Language Processing with Hybrid Explainability: A Technical Report Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T19:40:08.478976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b54bd189-56c8-4223-9302-983b7954b2b0 · inbound

RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Records cites this paper.

RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Records Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:57:02.892601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7024cd76-2a0d-4eac-b776-c3a1ede5c2a1 · inbound

ROVI: A VLM-LLM Re-Captioned Dataset for Open-Vocabulary Instance-Grounded Text-to-Image Generation cites this paper.

ROVI: A VLM-LLM Re-Captioned Dataset for Open-Vocabulary Instance-Grounded Text-to-Image Generation Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T05:59:15.577307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f64dd79-dd13-4aa9-8e38-938f8c73e991 · inbound

Enhancing User-Feedback Driven Requirements Prioritization cites this paper.

Enhancing User-Feedback Driven Requirements Prioritization Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T05:41:28.138682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 039b5968-8ca1-4652-b6f8-7ea7fb0fd891 · inbound

Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detection cites this paper.

Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detection Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-10T15:40:34.592246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e5847d92-bfea-4090-bc17-bd8a2c8cf169 · inbound

The TEA Nets framework combines AI and cognitive network science to model targets, events and actors in text cites this paper.

The TEA Nets framework combines AI and cognitive network science to model targets, events and actors in text Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:06:28.254265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 012520e9-91ea-4232-beec-d057fdc20fd4 · inbound

Methods, Data, and Conceptual Change: Reflections from Two Quantitative Diachronic Case Studies cites this paper.

Methods, Data, and Conceptual Change: Reflections from Two Quantitative Diachronic Case Studies Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-08T19:29:05.193593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 17681080-84a8-4349-b2b1-504d8fb574c6 · inbound

Parser agreement and disagreement in L2 Korean UD: Implications for human-in-the-loop annotation cites this paper.

Parser agreement and disagreement in L2 Korean UD: Implications for human-in-the-loop annotation Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:12.577452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 809ffd61-7647-4e45-97f4-c41ef4457d6d · inbound

Linguistic Productivity in Large Language Models: Models Coerce, but do not Preempt cites this paper.

Linguistic Productivity in Large Language Models: Models Coerce, but do not Preempt Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 190

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.766274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b637cf9b-bd2d-4aa8-b13d-efa47a49cfea · inbound

Do It Right! A Methodology for Successful NLP System Development cites this paper.

Do It Right! A Methodology for Successful NLP System Development Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-11T04:25:29.271082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc4fe401-1259-49af-bddd-8f2ad0c1c56f · inbound

Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution cites this paper.

Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-02T14:50:22.053224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.