47 citations · 52 across the 9 of their papers we have counts for
4 papers · 2 filters
Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective
Ping Yang, Junjie Wang, Ruyi Gan +6
We propose a new paradigm for zero-shot learners that is format agnostic, i.e., it is compatible with any format and applicable to a list of language tasks, such as text classifica…
Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
Jiaxing Zhang, Ruyi Gan, Junjie Wang +22
Nowadays, foundation models become one of fundamental infrastructures in artificial intelligence, paving ways to the general intelligence. However, the reality presents two urgent…
Towards No.1 in CLUE Semantic Matching Challenge: Pre-trained Language Model Erlangshen with Propensity-Corrected Loss
Junjie Wang, Yuxiang Zhang, Ping Yang +1
This report describes a pre-trained language model Erlangshen with propensity-corrected loss, the No.1 in CLUE Semantic Matching Challenge. In the pre-training stage, we construct…
Unified BERT for Few-shot Natural Language Understanding
Junyu Lu, Ping Yang, Ruyi Gan +2
Even as pre-trained language models share a semantic encoder, natural language understanding suffers from a diversity of output schemas. In this paper, we propose UBERT, a unified…