Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1903.03862.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T12:54:14.096747Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T17:16:04.649808Z
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 8157b9d3-7332-4378-9c3c-4df76cd728cd · inbound
Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis cites this paper.
Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T17:16:04.653645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 740a6b55-b23a-40f8-b0d6-714c5dfda2d6 · inbound
Understanding Undesirable Word Embedding Associations cites this paper.
Understanding Undesirable Word Embedding Associations Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T12:54:14.096747Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b776dc25-e00f-4cbd-99e7-bd4f9699bfc7 · inbound
A Survey on Bias and Fairness in Machine Learning cites this paper.
A Survey on Bias and Fairness in Machine Learning Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T11:36:53.022099Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f9c06e89-42dc-4d56-a7b6-3a8fb137fa6f · inbound
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual cites this paper.
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T10:42:14.494878Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9de08ba9-b3e7-4525-b3dd-6a101ae638f9 · inbound
Rotate King to get Queen: Word Relationships as Orthogonal Transformations in Embedding Space cites this paper.
Rotate King to get Queen: Word Relationships as Orthogonal Transformations in Embedding Space Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T05:55:00.596377Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9777d46d-45be-4f70-bf5c-71385a6ec3c8 · inbound
Language Models are Few-Shot Learners cites this paper.
Language Models are Few-Shot Learners Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T12:05:38.175809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c1719e29-d820-4c6f-9587-712ca937234f · inbound
Mitigating Gender Bias in Contextual Word Embeddings cites this paper.
Mitigating Gender Bias in Contextual Word Embeddings Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:02:56.146297Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 22126093-5702-4f7a-a2da-1abde12cbc1f · inbound
Operationalizing Fairness in Text-to-Image Models: A Survey of Bias, Fairness Audits and Mitigation Strategies cites this paper.
Operationalizing Fairness in Text-to-Image Models: A Survey of Bias, Fairness Audits and Mitigation Strategies Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T11:36:02.349365Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 8ba0ec56-3f97-4bdb-b583-4138113d4ac7 · inbound
Fairness Pruning: Locating Demographic Bias in GLU-MLP Layers via Differential Activations cites this paper.
Fairness Pruning: Locating Demographic Bias in GLU-MLP Layers via Differential Activations Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T11:25:39.315059Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.