16 citations · 28 across the 5 of their papers we have counts for
5 papers · 1 filter
EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo +6
Large Language Models (LLMs) excel in various tasks, but they rely on carefully crafted prompts that often demand substantial human effort. To automate this process, in this paper,…
Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation
Jiquan Li, Junliang Guo, Yongxin Zhu +4
The task of Grammatical Error Correction (GEC) has received remarkable attention with wide applications in Natural Language Processing (NLP) in recent years. While one of the key p…
Towards Variable-Length Textual Adversarial Attacks
Junliang Guo, Zhirui Zhang, Linlin Zhang +4
Adversarial attacks have shown the vulnerability of machine learning models, however, it is non-trivial to conduct textual adversarial attacks on natural language processing tasks…
Incorporating BERT into Parallel Sequence Decoding with Adapters
Junliang Guo, Zhirui Zhang, Linli Xu +3
While large scale pre-trained language models such as BERT have achieved great success on various natural language understanding tasks, how to efficiently and effectively incorpora…
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input
Junliang Guo, Xu Tan, Di He +3
Non-autoregressive translation (NAT) models, which remove the dependence on previous target tokens from the inputs of the decoder, achieve significantly inference speedup but at th…