Researchers from Beijing University of Posts and Telecommunication have introduced a novel visual dialogue state tracking (VDST) model that’s got pretty good at the similar, visual dialogue guessing game “GuessWhat?!”
Due to the nuanced character choices and other unique literal and aesthetical characteristics, automatic generation of Chinese poetry is challenging for AI, and high-quality poems can hardly be generated by end-to-end methods.
Carnegie Mellon University researchers have made another leap in the field with their Joint Language-to-Pose (JL2P) model, which generate animations from text input via a joint multimodal space comprising language and poses.
A team of researchers from Carnegie Mellon University and Google Brain have now proposed XLNet, a new language model which outperforms BERT on 20 language tasks including SQuAD, GLUE, and RACE; and has achieved SOTA results on 18 of these tasks.
Baidu has released ERNIE (Enhanced Representation through kNowledge IntEgration), a new knowledge integration language representation model which outperforms Google’s state-of-the-art BERT (Bidirectional Encoder Representations from Transformers) in Chinese language tasks.