Paper Citation Record · LEDGER

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks

As of 1 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 4 inbound Pith citation observations for arXiv:2502.04419.

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

pith.paper-citation-record.v1
2502.04419 v3

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-23T03:53:00.509414Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-01T06:32:01.292127+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T22:49:03.124658Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-06-28T22:52:45.523134Z

Reference resolution

44 of 44 outbound references displayed

verified exact21
verified fuzzy21
unresolved0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5f49515d-d79e-4eb4-8cfb-9ebc312b69ad · outbound

This paper cites Phi-4 Technical Report.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Phi-4 Technical Report

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-23T03:55:21.911213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 922ede37-ebb6-4baf-8953-181b1dd35375 · outbound

This paper cites Physics of Language Models: Part 3.1, Knowledge Storage and Extraction.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.891117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 4747ffc8-e229-4155-b11e-fd746416bd47 · outbound

This paper cites Overview of mex-a3t at ibereval 2018: Authorship and aggressiveness analysis in mexican spanish tweets.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Overview of mex-a3t at ibereval 2018: Authorship and aggressiveness analysis in mexican spanish tweets

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.343476Z

Source-reported events for the cited work

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Observation 384891be-0c0d-47ff-ba75-1a9a50e9e6ad · outbound

This paper cites Measuring Implicit Bias in Explicitly Unbiased Large Language Models.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Measuring Implicit Bias in Explicitly Unbiased Large Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.879588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation f27ff4a1-536a-4f01-b641-1df362127b57 · outbound

This paper cites Semeval-2019 task 5: Multilingual detection of hate speech against immigrants and women in twitter.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Semeval-2019 task 5: Multilingual detection of hate speech against immigrants and women in twitter

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.353664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 6107f8dc-2780-441a-8cc2-d62e17b18b43 · outbound

This paper cites Revealing Hidden Bias in AI: Lessons from Large Language Models.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Revealing Hidden Bias in AI: Lessons from Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.918365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 4b771d01-1630-4144-a638-b6d8975d1442 · outbound

This paper cites Language models are few-shot learners.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Language models are few-shot learners

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.356213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation c6b32a61-7784-426f-8313-d647dd1ef884 · outbound

This paper cites AGR: Age group fairness reward for bias mitigation in LLMs.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks AGR: Age group fairness reward for bias mitigation in LLMs

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.388992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation e56fdd23-24ca-46ad-8e30-d5f34d4c0296 · outbound

This paper cites URLhttps://aclanthology.org/2020.lrec-1.761/.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks URLhttps://aclanthology.org/2020.lrec-1.761/

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.345648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 9416f78d-23e2-4137-b857-6067f5c979f4 · outbound

This paper cites Data augmentation using llms: Data perspectives, learning paradigms and challenges.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Data augmentation using llms: Data perspectives, learning paradigms and challenges

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.348447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 6d06e287-e6b7-40db-8c58-ecbbabd2e380 · outbound

This paper cites Sina at FigNews 2024: Multilingual Datasets Annotated with Bias and Propaganda.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Sina at FigNews 2024: Multilingual Datasets Annotated with Bias and Propaganda

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.900421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 149613b7-e315-40ca-a6d7-6f6d4082f1b5 · outbound

This paper cites Towards Measuring the Representation of Subjective Global Opinions in Language Models.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Towards Measuring the Representation of Subjective Global Opinions in Language Models

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-23T03:55:21.894076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 90ae74cf-1825-4618-8036-92ebbba00b33 · outbound

This paper cites First-Person Fairness in Chatbots.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks First-Person Fairness in Chatbots

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.921936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation e12e55e4-c0a9-4c41-a113-4849c413a4cb · outbound

This paper cites Jillian Fisher, Shangbin Feng, Robert Aron, Thomas Richardson, Yejin Choi, Daniel W Fisher, Jennifer Pan, Yulia Tsvetkov, and Katharina Reinecke.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Jillian Fisher, Shangbin Feng, Robert Aron, Thomas Richardson, Yejin Choi, Daniel W Fisher, Jennifer Pan, Yulia Tsvetkov, and Katharina Reinecke

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.873189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation e4d1c963-08e5-423a-b865-fd059a5455e5 · outbound

This paper cites Modeling Human Subjectivity in LLMs Using Explicit and Implicit Human Factors in Personas.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Modeling Human Subjectivity in LLMs Using Explicit and Implicit Human Factors in Personas

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.919993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 8587fe5f-b75f-48c9-8ee0-027f8ebc1599 · outbound

This paper cites Hey GPT, Can You be More Racist? Analysis from Crowdsourced Attempts to Elicit Biased Content from Generative AI.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Hey GPT, Can You be More Racist? Analysis from Crowdsourced Attempts to Elicit Biased Content from Generative AI

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.889220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation f84421a6-54ef-48c6-976e-c4c7a7c0671d · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks LoRA: Low-Rank Adaptation of Large Language Models

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-23T03:55:21.925097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 59833ce8-cf64-4aa6-91a2-7ba64860836b · outbound

This paper cites Huggingface.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Huggingface

Reference 18

Resolution: verified exact; doi, observed 2026-05-23T03:55:21.700811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 5c4e54b9-aa56-40f0-97bf-8c2a19258704 · outbound

This paper cites URLhttps://aclanthology.org/2020.osact-1.8/.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks URLhttps://aclanthology.org/2020.osact-1.8/

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.376715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 472c9b56-d825-48ae-a341-0b4d197db65c · outbound

This paper cites Shovon, and Gene Kim.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Shovon, and Gene Kim

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.371395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 327b9d34-50e1-45b0-878c-37264f8b9b93 · outbound

This paper cites doi: 10.18653/v1/2024.findings-acl.530.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks doi: 10.18653/v1/2024.findings-acl.530

Reference 21

Resolution: verified exact; doi, observed 2026-05-23T03:55:21.715398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 0d9ace79-0cc5-4cd2-afe8-975950fefa54 · outbound

This paper cites Subtle biases need subtler measures: Dual metrics for evaluating representative and affinity bias in large language models.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Subtle biases need subtler measures: Dual metrics for evaluating representative and affinity bias in large language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.379725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 0513b694-593d-4f8d-a854-956a086452a3 · outbound

This paper cites Ruleprompt: Weakly supervised text classification with prompting plms and self-iterative logical rules.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Ruleprompt: Weakly supervised text classification with prompting plms and self-iterative logical rules

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.382969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 3b837be3-5946-469f-ab75-6761d8314b29 · outbound

This paper cites Chen Liu, Fajri Koto, Timothy Baldwin, and Iryna Gurevych.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Chen Liu, Fajri Koto, Timothy Baldwin, and Iryna Gurevych

Reference 24

Resolution: verified exact; doi, observed 2026-05-23T03:55:21.712194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 1d96d095-7c70-4498-bc0e-8e6dd08ad316 · outbound

This paper cites The generation gap: Exploring age bias in the value systems of large language models.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks The generation gap: Exploring age bias in the value systems of large language models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.371164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation cde44b65-113e-4441-8ddc-d5a3d2f603bd · outbound

This paper cites AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.368933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 84a321ac-336e-47b5-bf48-e2db02a37647 · outbound

This paper cites AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models.

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.863950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 3d3edaee-d305-4a89-9b71-13bccf96f3bd · outbound

This paper cites Text classification using label names only: A language model self-training approach.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Text classification using label names only: A language model self-training approach

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.358689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 390c7e7c-09b2-4edb-aeaf-47d8be059c25 · outbound

This paper cites Tarek Naous, Michael J Ryan, Alan Ritter, and Wei Xu.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Tarek Naous, Michael J Ryan, Alan Ritter, and Wei Xu

Reference 29

Resolution: verified exact; doi, observed 2026-05-23T03:55:21.704546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 75cd83ad-17da-4e4d-8de7-cc20d7be1c16 · outbound

This paper cites you gotta be a doctor, lin.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks you gotta be a doctor, lin

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.365617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 5b779e7e-bcca-4e19-b052-bca647e56469 · outbound

This paper cites Steven Rogulsky, Nicholas Popovic, and Michael Färber.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Steven Rogulsky, Nicholas Popovic, and Michael Färber

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.718989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 7555ef31-e65f-4d3e-873c-20ff10642be6 · outbound

This paper cites The bias amplification paradox in text-to-image generation.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks The bias amplification paradox in text-to-image generation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.365768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 6071184a-91f5-4464-a28c-871ae81e33aa · outbound

This paper cites Detection and measurement of syntactic templates in generated text.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Detection and measurement of syntactic templates in generated text

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.374304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation c85d53b5-131c-4da6-9f8d-b98ced7b3352 · outbound

This paper cites LLM Theory of Mind and Alignment: Opportunities and Risks.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks LLM Theory of Mind and Alignment: Opportunities and Risks

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.914832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation c7ca237a-e0d2-4117-a607-fc3f3d0c8afa · outbound

This paper cites Will we run out of data? Limits of LLM scaling based on human-generated data.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Will we run out of data? Limits of LLM scaling based on human-generated data

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-05-23T03:55:21.898749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation e128e0e0-77ba-49c6-b899-176f93d44837 · outbound

This paper cites Unraveling downstream gender bias from large language models: A study on AI educational writing assistance.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Unraveling downstream gender bias from large language models: A study on AI educational writing assistance

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.346583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation a903054b-3a5a-41cf-8385-4cfbe6bb697e · outbound

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

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks kelly is a warm person, joseph is a role model

Reference 37

Resolution: verified exact; doi, observed 2026-05-23T03:55:21.709591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 280703ef-5dd4-46e8-bf82-c5857f9d9d99 · outbound

This paper cites doi: 10.18653/v1/2023.findings-emnlp.243.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks doi: 10.18653/v1/2023.findings-emnlp.243

Reference 38

Resolution: verified exact; doi, observed 2026-05-23T03:55:21.707100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 3f3165c5-8934-48e8-baef-aba5c0e41a84 · outbound

This paper cites Will the Inclusion of Generated Data Amplify Bias Across Generations in Future Image Classification Models?.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Will the Inclusion of Generated Data Amplify Bias Across Generations in Future Image Classification Models?

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.904083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation c21a2c00-e6bd-4078-82a0-274f7877c901 · outbound

This paper cites How to Synthesize Text Data without Model Collapse?.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks How to Synthesize Text Data without Model Collapse?

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:55:21.915792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 5932ab21-1744-415e-a359-fb6e04749a56 · outbound

This paper cites You are a person influenced by Spanish culture responding to the following question.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks You are a person influenced by Spanish culture responding to the following question

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.340533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation d2a107ed-7d92-4194-9017-f6caffdf2de3 · outbound

This paper cites Generate a story about a character named [NAME].

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Generate a story about a character named [NAME]

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.355405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 09e64b81-178f-4662-8029-34aae8802a90 · outbound

This paper cites We extract these adjectives from the generated stories, analyzing the frequency of adjectives used to describe the characters.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks We extract these adjectives from the generated stories, analyzing the frequency of adjectives used to describe the characters

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.386123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 08175fe2-5dc9-49f4-9168-9ccedb52751d · outbound

This paper cites To ensure gender balance, we sample 600 examples for each profession, with an equal split between male and female data.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks To ensure gender balance, we sample 600 examples for each profession, with an equal split between male and female data

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T03:55:22.362281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Pith citing papers

Observation 9ef16029-748a-49a0-bd4a-b239353d1850 · inbound

Inertia in Moral and Value Judgments of Large Language Models cites this paper.

Inertia in Moral and Value Judgments of Large Language Models Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-23T22:05:50.183243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 3cb4a72c-281a-4e42-a32b-11a22413fc77 · inbound

Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs cites this paper.

Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-19T11:07:15.444706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation 964e8a14-58d4-4f7d-a979-1579318fc093 · inbound

Safe for Whom? Rethinking How We Evaluate the Safety of LLMs for Real Users cites this paper.

Safe for Whom? Rethinking How We Evaluate the Safety of LLMs for Real Users Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-16T23:23:39.906906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.

Observation bc8ea647-1a8b-4bc8-b3a0-eaa065ae412c · inbound

Every Act Has Its Price: Compressed Moral Composition in Frontier LLMs cites this paper.

Every Act Has Its Price: Compressed Moral Composition in Frontier LLMs Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks

Reference 145

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.524323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.