The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data | Paper Citation Record

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This paper cites Collapsed Language Models Promote Fairness.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Collapsed Language Models Promote Fairness

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Behavior research methods , volume=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Proceedings of the International Conference on Learning Representations (ICLR) , year=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data The Impact of AI-Generated Text on the Internet

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society , volume=

Reference 5

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This paper cites J ob F air: A Framework for Benchmarking Gender Hiring Bias in Large Language Models.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data J ob F air: A Framework for Benchmarking Gender Hiring Bias in Large Language Models

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data NAACL , year=

Reference 7

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data EMNLP , year=

Reference 8

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data IEEE Transactions on Knowledge and Data Engineering , year=

Reference 9

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This paper cites The Woman Worked as a Babysitter: On Biases in Language Generation.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data The Woman Worked as a Babysitter: On Biases in Language Generation

Reference 10

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This paper cites Proceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization , pages=.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Proceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization , pages=

Reference 11

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data proceedings of the Conference on Fairness, Accountability, and Transparency , pages=

Reference 12

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data ACL , year=

Reference 13

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data PNAS nexus , volume=

Reference 14

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This paper cites Linking artificial and human neural representations of language.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Linking artificial and human neural representations of language

Reference 15

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This paper cites A Tale of Tails: Model Collapse as a Change of Scaling Laws.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data A Tale of Tails: Model Collapse as a Change of Scaling Laws

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This paper cites Combining Generative Artificial Intelligence (AI) and the Internet: Heading towards Evolution or Degradation?.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Combining Generative Artificial Intelligence (AI) and the Internet: Heading towards Evolution or Degradation?

Reference 17

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This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 18

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This paper cites L a C o: Large Language Model Pruning via Layer Collapse.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data L a C o: Large Language Model Pruning via Layer Collapse

Reference 19

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Proceedings of the National Academy of Sciences , volume=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Ethical and social risks of harm from Language Models

Reference 21

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Proceedings of the 2021 ACM conference on fairness, accountability, and transparency , pages=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data International Conference on Learning Representations , volume=

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This paper cites What ' s in a Name? R educing Bias in Bios without Access to Protected Attributes.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data What ' s in a Name? R educing Bias in Bios without Access to Protected Attributes

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Towards Debiasing Sentence Representations

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data F air S teer: Inference Time Debiasing for LLM s with Dynamic Activation Steering

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Social Bias Probing: Fairness Benchmarking for Language Models

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data S tereo S et: Measuring stereotypical bias in pretrained language models

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data C row S -Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data How to Synthesize Text Data without Model Collapse?

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data , author=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Unresolved cited work

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Scaling Laws for Neural Language Models

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data POT Python Optimal Transport (version 0.9.5) , url =

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data arXiv preprint arXiv:2502.13595 , year=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data The Curse of Recursion: Training on Generated Data Makes Models Forget

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data International Conference on Learning Representations , volume=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data The Thirty-eighth Annual Conference on Neural Information Processing Systems , year=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Fine-Tuning Language Models with Just Forward Passes

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Advances in neural information processing systems , volume=

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data keynote at neurips , author=

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This paper cites Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods.

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods

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The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data Advances in neural information processing systems , volume=

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