A Survey on Deep Active Learning: Recent Advances and New Frontiers
Active learning seeks to achieve strong performance with fewer training samples. It does this
by iteratively asking an oracle to label newly selected samples in a human-in-the-loop …
by iteratively asking an oracle to label newly selected samples in a human-in-the-loop …
The best of both worlds: Combining human and machine translations for multilingual semantic parsing with active learning
Multilingual semantic parsing aims to leverage the knowledge from the high-resource
languages to improve low-resource semantic parsing, yet commonly suffers from the data …
languages to improve low-resource semantic parsing, yet commonly suffers from the data …
SCAR: Efficient Instruction-Tuning for Large Language Models via Style Consistency-Aware Response Ranking
Recent studies have shown that maintaining a consistent response style by human experts
and enhancing data quality in training sets can significantly improve the performance of fine …
and enhancing data quality in training sets can significantly improve the performance of fine …