3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 3 cited
Language Versatilists vs. Specialists: An Empirical Revisiting on Multilingual Transfer Ability
Jiacheng Ye, Xijia Tao, Lingpeng Kong
Multilingual transfer ability, which reflects how well the models fine-tuned on one source language can be applied to other languages, has been well studied in multilingual pre-tra…
cs.CL2023
Generating Data for Symbolic Language with Large Language Models
Jiacheng Ye, Chengzu Li, Lingpeng Kong +1
While large language models (LLMs) bring not only performance but also complexity, recent work has started to turn LLMs into data generators rather than task inferencers, where ano…
cs.CL2023★ 1 cited
OpenICL: An Open-Source Framework for In-context Learning
Zhenyu Wu, YaoXiang Wang, Jiacheng Ye +4
In recent years, In-context Learning (ICL) has gained increasing attention and emerged as the new paradigm for large language model (LLM) evaluation. Unlike traditional fine-tuning…