fairness

“Assuming the article argues that AI 'slop' originates from human input: "The garbage in, garbage out principle applies directly to AI training."”

“The context mentions the source of the article is ArXiv.”

“The paper focuses on removing bias without erasing demographics.”

“The context mentions the article is sourced from ArXiv, indicating it is a pre-print research paper.”

“The study focuses on empirically characterizing tone bias in LLM-driven UX systems.”

“The research focuses on 93 stigmatized groups.”

“The research focuses on the performance trade-offs associated with mitigating bias.”

“The article focuses on fair regression for multiple groups in the context of Chronic Kidney Disease.”

“The paper is available on ArXiv, suggesting peer review is not yet complete but the research is publicly accessible.”

“The paper focuses on bias and discrimination in memory-enhanced AI agents.”

“The article likely explores emergent bias and fairness within the context of multi-agent decision systems.”

“The study focuses on cross-language bias.”

“The paper focuses on vision-language models for medical image disease classification.”

“The research focuses on the bias of the Gini estimator in Poisson and geometric cases, also characterizing the gamma family and unbiasedness under gamma distributions.”

“The study utilizes interviews to gather insights.”

“The study explores the alignment of language models with specific cultural values and the effects of cultural prompting.”

“Overcoming Privileged Information Bias in Asymmetric Embodied Agents via Active Querying”

“BAID is a benchmark for bias assessment of AI detectors.”

“The article's context revolves around fairness-regularized online optimization with a focus on switching costs.”

“The research focuses on unbiased data collection for recommender systems.”

“The study focuses on mitigating bias in both English and Urdu language models.”

“The article explores representation invariance and allocation.”

“The context indicates an investigation into potential systematic biases within generative AI text annotations.”

“The study investigates fairness requirements in AI-enabled software engineering.”

“The context mentions Bita being a conversational assistant.”

“The article's focus is on addressing social degradation in pre-trained vision-language models.”

“The research focuses on the privacy, adversarial robustness, fairness, and ethics of Low-Rank LLMs.”

“Targeted bias reduction can exacerbate unmitigated LLM biases.”

“The research focuses on correcting mean bias in text embeddings.”

“The article expresses concern about machine learning in the judicial system.”