Paper Citation Record · LEDGER

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach

As of 13 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2411.17338.

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

pith.paper-citation-record.v1
2411.17338 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:21:33.984161Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

47 of 47 outbound references displayed

verified exact0
verified fuzzy24
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8ec3f64-1f74-4cb7-9b47-e546d401e7da · outbound

This paper cites Qwen Technical Report.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Qwen Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.815442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aad95988-76e8-4415-8c9b-811df9071370 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.819978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96c24cf7-bff9-4d06-81e6-52507e8bcf69 · outbound

This paper cites Assessing LLMs for Moral Value Pluralism.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Assessing LLMs for Moral Value Pluralism

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.824413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69e732e0-de58-4d3d-80d6-f66184ea4ca6 · outbound

This paper cites Toward a broader view of social stereotyping.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Toward a broader view of social stereotyping

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.498160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 71a5691d-4119-4886-a0d1-b543f701ed8b · outbound

This paper cites Man is to computer programmer as woman is to homemaker? debiasing word embeddings.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Man is to computer programmer as woman is to homemaker? debiasing word embeddings

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.832223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8d2e367-70a7-40e2-9458-56d700a5e2ed · outbound

This paper cites Ethnic stereotypes.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Ethnic stereotypes

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.481543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3567385d-096d-4240-8904-d0ea3ac5e0c0 · outbound

This paper cites Semantics derived automatically from language corpora contain human-like biases.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Semantics derived automatically from language corpora contain human-like biases

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.471999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dcc92eeb-a73b-432b-ac4e-c37195f3358d · outbound

This paper cites Attenuating bias in word vectors.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Attenuating bias in word vectors

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.461777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b205add7-5884-47ca-bc53-c72c204149a6 · outbound

This paper cites The Llama 3 Herd of Models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach The Llama 3 Herd of Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.846906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49bf05a4-a3fe-4e9e-b2e2-f525db367963 · outbound

This paper cites Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.850585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55fe97f9-5270-41bf-831c-46fb102b3ae7 · outbound

This paper cites Self-Debiasing Large Language Models: Zero-Shot Recognition and Reduction of Stereotypes.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Self-Debiasing Large Language Models: Zero-Shot Recognition and Reduction of Stereotypes

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.855131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 862812aa-8b63-482b-82fa-54b164a53283 · outbound

This paper cites Detecting emergent intersectional biases: Contextualized word embeddings contain a distribution of human-like biases.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Detecting emergent intersectional biases: Contextualized word embeddings contain a distribution of human-like biases

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.450823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fde9e2c5-b857-43c0-b41f-6a38d9ac864a · outbound

This paper cites Bias Runs Deep: Implicit reasoning biases in persona-assigned LLMs.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Bias Runs Deep: Implicit reasoning biases in persona-assigned LLMs

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.439554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1a4cf6a5-585b-4a19-9d7f-aa33e64eb108 · outbound

This paper cites Bias in social research.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Bias in social research

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.428514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 97568482-c7e2-44ab-8f65-876539fdc075 · outbound

This paper cites Mistral 7B.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Mistral 7B

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.869017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a85770ca-1775-45ee-b47e-2f5e35ba0967 · outbound

This paper cites Definition and assessment of accuracy in social stereotypes.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Definition and assessment of accuracy in social stereotypes

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.417663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0eeeb28f-9a6a-498d-8c24-6bfda220e8df · outbound

This paper cites Précis of social perception and social reality: Why accuracy dominates bias and self-fulfilling prophecy.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Précis of social perception and social reality: Why accuracy dominates bias and self-fulfilling prophecy

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.406643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7c42ddd1-d3ae-457b-b356-a70d1a678d73 · outbound

This paper cites Crawford, and Rachel S.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Crawford, and Rachel S

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.395906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ca103c0d-9517-4c5d-8bfe-86d7f765e647 · outbound

This paper cites Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.884850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation faae2927-d484-40a0-b297-de8ec3fea5b5 · outbound

This paper cites Gender bias and stereotypes in large language models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Gender bias and stereotypes in large language models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.889213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa282914-fbd0-4270-8fb8-ac191b815c8b · outbound

This paper cites Towards understanding and mitigating social biases in language models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Towards understanding and mitigating social biases in language models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.892524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ffce77d-4554-48c2-b7a0-00122bd02305 · outbound

This paper cites Holistic Evaluation of Language Models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Holistic Evaluation of Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.895762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 222404cb-2b5b-40c1-b609-aa5246a45063 · outbound

This paper cites Harmbench: A standardized evaluation framework for automated red teaming and robust refusal.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Harmbench: A standardized evaluation framework for automated red teaming and robust refusal

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.371316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation da0fb5f3-cb0b-4785-b83e-526e1807e100 · outbound

This paper cites StereoSet: Measuring stereotypical bias in pretrained language models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach StereoSet: Measuring stereotypical bias in pretrained language models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.902740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82e6bce3-b21a-4cb4-a86c-a90788acc916 · outbound

This paper cites CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.906347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd9de3a8-5068-4da2-bbe6-7518ae4b8947 · outbound

This paper cites In-contextual gender bias suppression for large language models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach In-contextual gender bias suppression for large language models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.360251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d5eca132-019d-4bd3-8bfc-770c63dec214 · outbound

This paper cites Usage policies.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Usage policies

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.349529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 656c4232-068e-4c87-a96b-c6d6ddfd18a8 · outbound

This paper cites Training language models to follow instructions with human feedback.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Training language models to follow instructions with human feedback

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.917304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aaebf3c4-9492-4cab-97ed-50182edd6cf8 · outbound

This paper cites BBQ: A hand-built bias benchmark for question answering.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach BBQ: A hand-built bias benchmark for question answering

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.332275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c55ed186-3b1a-4bbd-8f66-e50d951bb63b · outbound

This paper cites Discovering Language Model Behaviors with Model-Written Evaluations.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Discovering Language Model Behaviors with Model-Written Evaluations

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.924099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 142b0571-93b1-43f0-9bed-383fe2050904 · outbound

This paper cites Estelle Smith, Bryan Semaan, Shaimaa Lazem, Robert Soden, Michael Muller, and Syed Ishtiaque Ahmed.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Estelle Smith, Bryan Semaan, Shaimaa Lazem, Robert Soden, Michael Muller, and Syed Ishtiaque Ahmed

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.322213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 44503f4f-d2d6-436f-b5bd-537b171926e1 · outbound

This paper cites Gender bias in coreference resolution.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Gender bias in coreference resolution

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.311900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 08f4da56-068b-44ad-ac90-048b6057b43a · outbound

This paper cites Stereotype accuracy.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Stereotype accuracy

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.301179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 17595ff3-8b52-4c15-861f-3c900addae34 · outbound

This paper cites what shapes your bias?.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach what shapes your bias?

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.290527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ac3a2072-0657-4fc3-a626-bf8dc3cdb59b · outbound

This paper cites "I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Dataset.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach "I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Dataset

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.941833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22d40397-c13d-4ead-ab85-02673ecea954 · outbound

This paper cites Value kaleidoscope: Engaging ai with pluralistic human values, rights, and duties.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Value kaleidoscope: Engaging ai with pluralistic human values, rights, and duties

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.279443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 06c78b3a-e2f3-4c77-8e29-c2981ba2879a · outbound

This paper cites A Roadmap to Pluralistic Alignment.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach A Roadmap to Pluralistic Alignment

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.948770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38a268ba-aa78-48f3-8b0b-7134734f2f7e · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.952841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7685c4a-22d4-4514-b5f7-f192d8ba410d · outbound

This paper cites Labor Force Statistics from the Current Population Survey.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Labor Force Statistics from the Current Population Survey

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.267256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 192be9dd-4f3d-4acc-8499-0b5a0496c481 · outbound

This paper cites On Evaluating and Mitigating Gender Biases in Multilingual Settings.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach On Evaluating and Mitigating Gender Biases in Multilingual Settings

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.959610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ef64ed4-80fb-4321-ad2b-2a2b2dccae45 · outbound

This paper cites kelly is a warm person, joseph is a role model.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach kelly is a warm person, joseph is a role model

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.256459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5694f23f-28b9-449f-a821-4f6794f76bd1 · outbound

This paper cites Do-not-answer: Evaluating safeguards in LLMs.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Do-not-answer: Evaluating safeguards in LLMs

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.244965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4fbbec23-b055-421b-ab83-3397b973ac90 · outbound

This paper cites JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.969888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 185a1ac8-a6d9-47a5-b79d-ea3105fc0d39 · outbound

This paper cites Qwen2 Technical Report.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Qwen2 Technical Report

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:33.973503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c79fbfd1-8a2a-405e-ad3f-0b95b440700e · outbound

This paper cites Gender bias in coreference resolution: Evaluation and debiasing methods.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Gender bias in coreference resolution: Evaluation and debiasing methods

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.234489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7047fbc3-f476-4d60-8833-a2703e0322b8 · outbound

This paper cites Learning gender-neutral word embed- dings.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Learning gender-neutral word embed- dings

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:21:34.223444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7e49273c-b761-41e1-91a3-58b4c53e088e · outbound

This paper cites Balancing Enhancement, Harmlessness, and General Capabilities: Enhancing Conversational LLMs with Direct RLHF.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Balancing Enhancement, Harmlessness, and General Capabilities: Enhancing Conversational LLMs with Direct RLHF

Reference 47

Resolution: metadata mismatch; local_arxiv, observed 2026-08-12T12:21:34.023116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.