107 citations · 157 across the 11 of their papers we have counts for
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cs.CL2023★ 4 cited
OccuQuest: Mitigating Occupational Bias for Inclusive Large Language Models
Mingfeng Xue, Dayiheng Liu, Kexin Yang +5
The emergence of large language models (LLMs) has revolutionized natural language processing tasks. However, existing instruction-tuning datasets suffer from occupational bias: the…
cs.CL2023★ 5 cited
How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition
Guanting Dong, Hongyi Yuan, Keming Lu +7
Large language models (LLMs) with enormous pre-training tokens and parameters emerge diverse abilities, including math reasoning, code generation, and instruction following. These…