Demos
These are some of the open-source demos we built to make our research more readily available for developers and researchers.
AK Hugging Face Paper Selection Predictor
Predict if @_akhaliq will select a paper into Hugging Face papers based on its title, authors, and abstract. demo code data models | |
OpenAI Watch
Monitoring the consistency of GPT-4 under greedy decoding (T=0) with a web-based application that commands GPT-4 to draw a unicorn every hour. demo data | |
Markup-to-Image Diffusion Models with Scheduled Sampling
A learning-based system to compilepresentational markup, such as LaTeX, into corresponding images. demo code paper models | |
Neural Linguistic Steganography
Hide secret messages in fluent texts using arithmetic coding and strong neural models. demo code paper | |
OpenNMT
A full service open-source neural machine translation system. Originally developed in Lua with Systran, since ported to PyTorch and TensorFlow and maintained externally. code paper | |
Image-to-Markup
A learning-based system to decompile an image into presentational markup. For example, we can infer the LaTeX or HTML source from a rendered image. demo code paper data models | |
Cascaded Text Generation with Markov Transformers
A parallel, fast, autoregressive, and accurate text generation algorithm using high-order Conditional Random Fields (CRFs). code paper |