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Tag

#fairness

6 articles tagged #fairness

arxivMay 15

Temporal Fair Division in Multi-Agent Systems: From Precise Alternation Metrics to Scalable Coordination Proxies

arXiv:2605.14879v1 Announce Type: cross Abstract: A plethora real-world environments require agents to compete repeatedly for the same limited resource, calling for a temporal notion of fairness judged across entire interaction histories. This paper advances the theory of temporal fair division by i

#multiagent#fairness#game-theoryRead on arxiv →
arxivApr 29

FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment

arXiv:2604.23786v1 Announce Type: new Abstract: In recent years, the integration of multimodal machine learning in wellbeing assessment has offered transformative potential for monitoring mental health. However, with the rapid advancement of Vision-Language Models (VLMs), their deployment in clinica

PHQW2 models#fairness#explainability#multimodalRead on arxiv →
arxivApr 24

Fairness-Aware Multi-Group Target Detection in Online Discussion

arXiv:2407.11933v4 Announce Type: replace Abstract: Target-group detection is the task of detecting which group(s) a piece of content is ``directed at or about''. Applications include targeted marketing, content recommendation, and group-specific content assessment. Key challenges include: 1) that a

#fairness#toxicity#machine-learningRead on arxiv →
arxivApr 17

Beyond Arrow's Impossibility: Fairness as an Emergent Property of Multi-Agent Collaboration

arXiv:2604.13705v1 Announce Type: cross Abstract: Fairness in language models is typically studied as a property of a single, centrally optimized model. As large language models become increasingly agentic, we propose that fairness emerges through interaction and exchange. We study this via a contro

RA1 model#fairness#multiagent#language-modelsRead on arxiv →
arxivApr 4

Fair Representation in Parliamentary Summaries: Measuring and Mitigating Inclusion Bias

arXiv:2507.14221v2 Announce Type: replace-cross Abstract: The The use of Large language models (LLMs) to summarise parliamentary proceedings presents a promising means of increasing the accessibility of democratic participation. However, as these systems increasingly mediate access to political info

LA1 model#fairness#bias#summarisationRead on arxiv →
arxivApr 3bearish

How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Models

arXiv:2511.06676v2 Announce Type: replace Abstract: Now that AI-driven moderation has become pervasive in everyday life, we often hear claims that "the AI is biased". While this is often said jokingly, the light-hearted remark reflects a deeper concern. How can we be certain that an online post flag

UN1 model#bias#fairness#language-modelsRead on arxiv →
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