47 citations · 102 across the 15 of their papers we have counts for
10 papers · 1 filter
Ziya-Visual: Bilingual Large Vision-Language Model via Multi-Task Instruction Tuning
Junyu Lu, Dixiang Zhang, Xiaojun Wu +5
Recent advancements enlarge the capabilities of large language models (LLMs) in zero-shot image-to-text generation and understanding by integrating multi-modal inputs. However, suc…
UniEX: An Effective and Efficient Framework for Unified Information Extraction via a Span-extractive Perspective
Ping Yang, Junyu Lu, Ruyi Gan +4
We propose a new paradigm for universal information extraction (IE) that is compatible with any schema format and applicable to a list of IE tasks, such as named entity recognition…
Enhancing Text Generation with Cooperative Training
Tong Wu, Hao Wang, Zhongshen Zeng +3
Recently, there has been a surge in the use of generated data to enhance the performance of downstream models, largely due to the advancements in pre-trained language models. Howev…
Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehension
Nuo Chen, Hongguang Li, Junqing He +8
The conversational machine reading comprehension (CMRC) task aims to answer questions in conversations, which has been a hot research topic in recent years because of its wide appl…
TCBERT: A Technical Report for Chinese Topic Classification BERT
Ting Han, Kunhao Pan, Xinyu Chen +5
Bidirectional Encoder Representations from Transformers or BERT~\cite{devlin-etal-2019-bert} has been one of the base models for various NLP tasks due to its remarkable performance…
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…
Solving Math Word Problems via Cooperative Reasoning induced Language Models
Xinyu Zhu, Junjie Wang, Lin Zhang +4
Large-scale pre-trained language models (PLMs) bring new opportunities to challenging problems, especially those that need high-level intelligence, such as the math word problem (M…
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…
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…
BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model
Hongyi Yuan, Zheng Yuan, Ruyi Gan +3
Pretrained language models have served as important backbones for natural language processing. Recently, in-domain pretraining has been shown to benefit various domain-specific dow…