Beyond autoregressive text generation
[Update 2022 Dec. 4] Added contrastive learning / decoding methods. [Update 2023 Mar. 10] Refactor and adding RLHF and diffusion methods. [Update 2023 Dec. 22] Added DPO, RAG and EMNLP 2023 papers. Intro The task of generating content from deep learning models is different from other common tasks in the sens that 1) the model is often trained to replicate the training data for continuous models or predict the next element for discrete ones; 2) when testing a model, there is no exact expected results, in consequence; 3) its evaluation is often tricky....