activity
20182022
most citedUnderstanding and Improving Layer Normalization

178 citations · 343 across the 10 of their papers we have counts for

collaborators
Showing cs.CLShow all

21 papers · 1 filter

cs.CL20211 cited

Learning Relation Alignment for Calibrated Cross-modal Retrieval

Shuhuai Ren, Junyang Lin, Guangxiang Zhao +5

Despite the achievements of large-scale multimodal pre-training approaches, cross-modal retrieval, e.g., image-text retrieval, remains a challenging task. To bridge the semantic ga…

cs.CL2021

Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation

Peng Wang, Junyang Lin, An Yang +4

Table-to-text generation refers to generating a descriptive text from a key-value table. Traditional autoregressive methods, though can generate text with high fluency, suffer from…

cs.CL2021

M6: A Chinese Multimodal Pretrainer

Junyang Lin, Rui Men, An Yang +22

In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1.9TB images and 292GB texts that cover a wide range of domains. We pro…

cs.CL202010 cited

Graph-based Multi-hop Reasoning for Long Text Generation

Liang Zhao, Jingjing Xu, Junyang Lin +3

Long text generation is an important but challenging task.The main problem lies in learning sentence-level semantic dependencies which traditional generative models often suffer fr…

cs.CL2020

InterBERT: Vision-and-Language Interaction for Multi-modal Pretraining

Junyang Lin, An Yang, Yichang Zhang +3

Multi-modal pretraining for learning high-level multi-modal representation is a further step towards deep learning and artificial intelligence. In this work, we propose a novel mod…

cs.CL201977 cited

Explicit Sparse Transformer: Concentrated Attention Through Explicit Selection

Guangxiang Zhao, Junyang Lin, Zhiyuan Zhang +3

Self-attention based Transformer has demonstrated the state-of-the-art performances in a number of natural language processing tasks. Self-attention is able to model long-term depe…