Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-10T17:09:43.892161Z
Paper Citation Record · LEDGER
From Ground Truth to Measurement: A Statistical Framework for Human Labeling
As of 4 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2604.07591.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T23:26:01.657217Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
28 of 28 outbound references displayed
- verified exact14
- verified fuzzy9
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 59451e2a-0cf3-4e20-9a2c-d22f20acf114 · outbound
This paper cites Order effects in annotation tasks: Further evidence of annotation sensitivity.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Order effects in annotation tasks: Further evidence of annotation sensitivity
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:45.991997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a0d4ebd1-0c50-4cfa-af4b-0ff862bf1ea3 · outbound
This paper cites Fair inference on error-prone outcomes.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Fair inference on error-prone outcomes
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.149079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1e0c58d2-fd0e-4012-b181-6a537f71ac33 · outbound
This paper cites You Are What You Annotate: Towards Better Models through Annotator Representations.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling You Are What You Annotate: Towards Better Models through Annotator Representations
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.190700Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fcdce837-e745-4df8-9135-967dcaeea4ce · outbound
This paper cites The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.110295Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 38689a52-07da-450a-aa04-1389effcbf42 · outbound
This paper cites "Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling "Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.097094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 46506a41-a753-4701-90ea-262c2a5e2a13 · outbound
This paper cites Sources of Uncertainty in Supervised Machine Learning -- A Statisticians' View.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Sources of Uncertainty in Supervised Machine Learning -- A Statisticians' View
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.164908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation da1dec7c-34a9-426b-a754-41607b5e7a48 · outbound
This paper cites Litex: A linguistic taxonomy of explanations for understanding within-label variation in natural language inference.arXiv preprint arXiv:2505.22848.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Litex: A linguistic taxonomy of explanations for understanding within-label variation in natural language inference.arXiv preprint arXiv:2505.22848
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.160834Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cd574033-be5b-4e96-ad7c-fbf0c38e4105 · outbound
This paper cites Jacobs and Hanna Wallach.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Jacobs and Hanna Wallach
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:46.002128Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2af54709-9f33-4382-b36f-c8f46f8781ef · outbound
This paper cites Jacobs and Hanna Wallach.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Jacobs and Hanna Wallach
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T17:10:37.875059Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b8702509-9fb6-474a-a16c-d684df5e61e1 · outbound
This paper cites Ecologically valid explanations for label variation in NLI.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Ecologically valid explanations for label variation in NLI
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:45.989078Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation abff0bdc-ca4c-4d40-884d-bbea103651e9 · outbound
This paper cites doi: 10.18653/v1/2023.findings-emnlp.712.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling doi: 10.18653/v1/2023.findings-emnlp.712
Reference 11
- Resolution
- verified exact
- doi, observed 2026-05-10T17:10:37.881536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 535c6717-76cf-4bdd-b27f-f2f1ace8b762 · outbound
This paper cites an unresolved cited work.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T11:51:45.983183Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d90bc899-3e5c-4e07-a54a-2b767100fccb · outbound
This paper cites doi: 10.18653/v1/2020.emnlp-main.734.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling doi: 10.18653/v1/2020.emnlp-main.734
Reference 13
- Resolution
- verified exact
- doi, observed 2026-05-10T17:10:37.878547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6ab65b85-5c4e-4d4d-94e1-e3d4bb772199 · outbound
This paper cites "Is a picture of a bird a bird": Policy recommendations for dealing with ambiguity in machine vision models.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling "Is a picture of a bird a bird": Policy recommendations for dealing with ambiguity in machine vision models
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.127632Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5c2861bd-ecd2-4fa5-b7dc-a8bee29880bb · outbound
This paper cites Making deep neural networks robust to label noise: A loss correction approach.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Making deep neural networks robust to label noise: A loss correction approach
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:45.985984Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 897c8d06-5189-4c2b-818e-dc7c23a74d2b · outbound
This paper cites When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN Dataset.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN Dataset
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.198158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0fa68997-5ce4-4b6f-8542-71b4187c96c1 · outbound
This paper cites The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.105755Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b0bc9fb4-1fb8-45ce-92a7-a94fc84b1a2f · outbound
This paper cites Perturbing the per- spective: How explanation impacts annotator labels.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Perturbing the per- spective: How explanation impacts annotator labels
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:45.998661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation eb4211f7-082c-476e-b6b4-ff276317fce9 · outbound
This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Sentence-bert: Sentence embeddings using siamese bert-networks
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:45.995443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cbce2f69-7822-45f5-be85-5992afedb8af · outbound
This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Reference 20
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T07:30:58.176351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 042b1966-880a-4c3d-a492-e70b0bcab65f · outbound
This paper cites an unresolved cited work.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T11:51:46.005410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f8bed61c-a800-44a5-89ef-d12395452084 · outbound
This paper cites doi: 10.18653/v1/2022.naacl-main.431.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling doi: 10.18653/v1/2022.naacl-main.431
Reference 22
- Resolution
- verified exact
- doi, observed 2026-05-10T17:10:37.884940Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d5247a6e-781c-47f8-984f-97064f97213d · outbound
This paper cites Cheap and fast–but is it good? evaluating non-expert annotations for natural language tasks.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Cheap and fast–but is it good? evaluating non-expert annotations for natural language tasks
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:45.974979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8c2eba85-33dd-488b-940a-0e0321f5f49c · outbound
This paper cites Alexandra Uma, Tommaso Fornaciari, Silviu Paun, Barbara Plank, Dirk Hovy, and Massimo Poesio.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Alexandra Uma, Tommaso Fornaciari, Silviu Paun, Barbara Plank, Dirk Hovy, and Massimo Poesio
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:46.008647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e1116046-03f9-40e2-9144-9a0d98caa63a · outbound
This paper cites Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T07:30:58.092181Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9b126dcc-f6c4-4929-a95d-991d6eb038d4 · outbound
This paper cites URLhttps://aclanthology.org/2024.acl-long.123/.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling URLhttps://aclanthology.org/2024.acl-long.123/
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T11:51:45.980579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a5a85e24-e9a9-4078-8b11-5891e6546268 · outbound
This paper cites Don't Waste a Single Annotation: Improving Single-Label Classifiers Through Soft Labels.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Don't Waste a Single Annotation: Improving Single-Label Classifiers Through Soft Labels
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:30:58.137949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 70c6dce4-43b2-40fc-aee6-3ee1da341600 · outbound
This paper cites an unresolved cited work.
From Ground Truth to Measurement: A Statistical Framework for Human Labeling Unresolved cited work
Reference 28
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T11:51:45.977914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
Observation f1c0ed9b-8d26-4861-9a04-aa4b606922ca · inbound
Design-Based Supervised Learning with Noisy Human Labels cites this paper.
Design-Based Supervised Learning with Noisy Human Labels From Ground Truth to Measurement: A Statistical Framework for Human Labeling
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T23:26:01.657217Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.