activity
20202023
most citedBoosting Distributed Training Performance of the Unpadded BERT Model

4 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2023★ 1 cited

Multimodal Zero-Shot Learning for Tactile Texture Recognition

Guanqun Cao, Jiaqi Jiang, Danushka Bollegala +2

Tactile sensing plays an irreplaceable role in robotic material recognition. It enables robots to distinguish material properties such as their local geometry and textures, especia…

eess.AS2022★ 1 cited

Peak-First CTC: Reducing the Peak Latency of CTC Models by Applying Peak-First Regularization

Zhengkun Tian, Hongyu Xiang, Min Li +3

The CTC model has been widely applied to many application scenarios because of its simple structure, excellent performance, and fast inference speed. There are many peaks in the pr…

cs.CV2022

Fast geometric trim fitting using partial incremental sorting and accumulation

Min Li, Laurent Kneip

We present an algorithmic contribution to improve the efficiency of robust trim-fitting in outlier affected geometric regression problems. The method heavily relies on the quick so…

cs.DC2022★ 4 cited

Boosting Distributed Training Performance of the Unpadded BERT Model

Jinle Zeng, Min Li, Zhihua Wu +4

Pre-training models are an important tool in Natural Language Processing (NLP), while the BERT model is a classic pre-training model whose structure has been widely adopted by foll…

cs.CL2020

KddRES: A Multi-level Knowledge-driven Dialogue Dataset for Restaurant Towards Customized Dialogue System

Hongru Wang, Min Li, Zimo Zhou +2

Compared with CrossWOZ (Chinese) and MultiWOZ (English) dataset which have coarse-grained information, there is no dataset which handle fine-grained and hierarchical level informat…