188 citations · 226 across the 4 of their papers we have counts for
4 papers
A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models
Junjie Ye, Xuanting Chen, Nuo Xu +12
GPT series models, such as GPT-3, CodeX, InstructGPT, ChatGPT, and so on, have gained considerable attention due to their exceptional natural language processing capabilities. Howe…
How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks
Xuanting Chen, Junjie Ye, Can Zu +7
The GPT-3.5 models have demonstrated impressive performance in various Natural Language Processing (NLP) tasks, showcasing their strong understanding and reasoning capabilities. Ho…
Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER
Ruotian Ma, Xuanting Chen, Lin Zhang +6
As the categories of named entities rapidly increase, the deployed NER models are required to keep updating toward recognizing more entity types, creating a demand for class-increm…
Searching for Optimal Subword Tokenization in Cross-domain NER
Ruotian Ma, Yiding Tan, Xin Zhou +6
Input distribution shift is one of the vital problems in unsupervised domain adaptation (UDA). The most popular UDA approaches focus on domain-invariant representation learning, tr…