The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

Natural language processing (NLP) is a subfield of artificial intelligence that focuses on
enabling computers to understand and process human languages. In the last five years, we …

Human motion is fundamental to understanding behavior. Despite progress on single-image
3D pose and shape estimation, existing video-based state-of-the-art methods fail to produce …

Large-scale language models often learn behaviors that are misaligned with user
expectations. Generated text may contain offensive or toxic language, contain significant …

Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …

We propose an adversarial training procedure for learning a causal implicit generative
model for a given causal graph. We show that adversarial training can be used to learn a …

Recent studies have shown that reinforcement learning (RL) is an effective approach for
improving the performance of neural machine translation (NMT) system. However, due to its …

This paper proposes an approach for applying GANs to NMT. We build a conditional
sequence generative adversarial net which comprises of two adversarial sub models, a …

Sign languages are multi-channel visual languages, where signers use a continuous 3D
space to communicate. Sign language production (SLP), the automatic translation from …

Teaching is critical to human society: it is with teaching that prospective students are
educated and human civilization can be inherited and advanced. A good teacher not only …