7 citations · 14 across the 8 of their papers we have counts for
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cs.AI2024★ 4 cited
Bias Amplification: Large Language Models as Increasingly Biased Media
Ze Wang, Zekun Wu, Jeremy Zhang +5
Model collapse, a phenomenon characterized by performance degradation due to iterative training on synthetic data, has been widely studied. However, its implications for bias ampli…
cs.CY2024★ 7 cited
Surveying Attitudinal Alignment Between Large Language Models Vs. Humans Towards 17 Sustainable Development Goals
Qingyang Wu, Ying Xu, Tingsong Xiao +8
Large Language Models (LLMs) have emerged as potent tools for advancing the United Nations' Sustainable Development Goals (SDGs). However, the attitudinal disparities between LLMs…