3 citations · 10 across the 14 of their papers we have counts for
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stat.ML2023★ 2 cited
Annotation Sensitivity: Training Data Collection Methods Affect Model Performance
Christoph Kern, Stephanie Eckman, Jacob Beck +3
When training data are collected from human annotators, the design of the annotation instrument, the instructions given to annotators, the characteristics of the annotators, and th…
cs.CL2023
Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models
Zheyu Zhang, Han Yang, Bolei Ma +2
Large Language Models (LLMs) demonstrate remarkable performance on a variety of natural language understanding (NLU) tasks, primarily due to their in-context learning ability. This…
cs.CL2023★ 2 cited
Is Prompt-Based Finetuning Always Better than Vanilla Finetuning? Insights from Cross-Lingual Language Understanding
Bolei Ma, Ercong Nie, Helmut Schmid +1
Multilingual pretrained language models (MPLMs) have demonstrated substantial performance improvements in zero-shot cross-lingual transfer across various natural language understan…