9 citations · 13 across the 7 of their papers we have counts for
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cs.CL2023
You Are What You Annotate: Towards Better Models through Annotator Representations
Naihao Deng, Xinliang Frederick Zhang, Siyang Liu +3
Annotator disagreement is ubiquitous in natural language processing (NLP) tasks. There are multiple reasons for such disagreements, including the subjectivity of the task, difficul…
cs.CL2023★ 9 cited
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
Oana Ignat, Zhijing Jin, Artem Abzaliev +19
Recent progress in large language models (LLMs) has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse t…