79 citations · 195 across the 8 of their papers we have counts for
5 papers · 1 filter
Multi-Vector Retrieval as Sparse Alignment
Yujie Qian, Jinhyuk Lee, Sai Meher Karthik Duddu +5
Multi-vector retrieval models improve over single-vector dual encoders on many information retrieval tasks. In this paper, we cast the multi-vector retrieval problem as sparse alig…
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding
Yanan Zheng, Jing Zhou, Yujie Qian +7
The few-shot natural language understanding (NLU) task has attracted much recent attention. However, prior methods have been evaluated under a disparate set of protocols, which hin…
GPT Understands, Too
Xiao Liu, Yanan Zheng, Zhengxiao Du +4
Prompting a pretrained language model with natural language patterns has been proved effective for natural language understanding (NLU). However, our preliminary study reveals that…
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
Zhengxiao Du, Yujie Qian, Xiao Liu +4
There have been various types of pretraining architectures including autoencoding models (e.g., BERT), autoregressive models (e.g., GPT), and encoder-decoder models (e.g., T5). How…
GraphIE: A Graph-Based Framework for Information Extraction
Yujie Qian, Enrico Santus, Zhijing Jin +2
Most modern Information Extraction (IE) systems are implemented as sequential taggers and only model local dependencies. Non-local and non-sequential context is, however, a valuabl…