4 citations · 11 across the 7 of their papers we have counts for
11 papers
Calibrating Factual Knowledge in Pretrained Language Models
Qingxiu Dong, Damai Dai, Yifan Song +3
Previous literature has proved that Pretrained Language Models (PLMs) can store factual knowledge. However, we find that facts stored in the PLMs are not always correct. It motivat…
Robust Fine-tuning via Perturbation and Interpolation from In-batch Instances
Shoujie Tong, Qingxiu Dong, Damai Dai +4
Fine-tuning pretrained language models (PLMs) on downstream tasks has become common practice in natural language processing. However, most of the PLMs are vulnerable, e.g., they ar…
StableMoE: Stable Routing Strategy for Mixture of Experts
Damai Dai, Li Dong, Shuming Ma +4
The Mixture-of-Experts (MoE) technique can scale up the model size of Transformers with an affordable computational overhead. We point out that existing learning-to-route MoE metho…
Mixture of Experts for Biomedical Question Answering
Damai Dai, Wenbin Jiang, Jiyuan Zhang +5
Biomedical Question Answering (BQA) has attracted increasing attention in recent years due to its promising application prospect. It is a challenging task because the biomedical qu…
Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot Event Classification
Peiyi Wang, Runxin Xu, Tianyu Liu +3
Few-Shot Event Classification (FSEC) aims at developing a model for event prediction, which can generalize to new event types with a limited number of annotated data. Existing FSEC…
Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehension
Damai Dai, Hua Zheng, Zhifang Sui +1
Conventional Machine Reading Comprehension (MRC) has been well-addressed by pattern matching, but the ability of commonsense reasoning remains a gap between humans and machines. Pr…