57 citations · 190 across the 32 of their papers we have counts for
5 papers · 1 filter
Demystifying Instruction Mixing for Fine-tuning Large Language Models
Renxi Wang, Haonan Li, Minghao Wu +4
Instruction tuning significantly enhances the performance of large language models (LLMs) across various tasks. However, the procedure to optimizing the mixing of instruction datas…
NADI 2023: The Fourth Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, AbdelRahim Elmadany, Chiyu Zhang +3
We describe the findings of the fourth Nuanced Arabic Dialect Identification Shared Task (NADI 2023). The objective of NADI is to help advance state-of-the-art Arabic NLP by creati…
The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages
Chiyu Zhang, Khai Duy Doan, Qisheng Liao +1
Instruction tuned large language models (LLMs), such as ChatGPT, demonstrate remarkable performance in a wide range of tasks. Despite numerous recent studies that examine the perfo…
What Constitutes Good Contrastive Learning in Time-Series Forecasting?
Chiyu Zhang, Qi Yan, Lili Meng +1
In recent years, the introduction of self-supervised contrastive learning (SSCL) has demonstrated remarkable improvements in representation learning across various domains, includi…
LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
Minghao Wu, Abdul Waheed, Chiyu Zhang +2
Large language models (LLMs) with instruction fine-tuning demonstrate superior generative capabilities. However, these models are resource-intensive. To alleviate this issue, we ex…