156 citations · 206 across the 4 of their papers we have counts for
4 papers
GEM: A General Evaluation Benchmark for Multimodal Tasks
Lin Su, Nan Duan, Edward Cui +7
In this paper, we present GEM as a General Evaluation benchmark for Multimodal tasks. Different from existing datasets such as GLUE, SuperGLUE, XGLUE and XTREME that mainly focus o…
M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training
Minheng Ni, Haoyang Huang, Lin Su +6
We present M3P, a Multitask Multilingual Multimodal Pre-trained model that combines multilingual pre-training and multimodal pre-training into a unified framework via multitask pre…
ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data
Di Qi, Lin Su, Jia Song +3
In this paper, we introduce a new vision-language pre-trained model -- ImageBERT -- for image-text joint embedding. Our model is a Transformer-based model, which takes different mo…
Gini-regularized Optimal Transport with an Application to Spatio-Temporal Forecasting
Lucas Roberts, Leo Razoumov, Lin Su +1
Rapidly growing product lines and services require a finer-granularity forecast that considers geographic locales. However the open question remains, how to assess the quality of a…