5 citations · 5 across the 2 of their papers we have counts for
4 papers
Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events
Le Fang, Tao Zeng, Chaochun Liu +3
Large-scale pretrained language models have shown thrilling generation capabilities, especially when they generate consistent long text in thousands of words with ease. However, us…
Transformer-based Conditional Variational Autoencoder for Controllable Story Generation
Le Fang, Tao Zeng, Chaochun Liu +3
We investigate large-scale latent variable models (LVMs) for neural story generation -- an under-explored application for open-domain long text -- with objectives in two threads: g…
Unsupervised Community Detection with a Potts Model Hamiltonian, an Efficient Algorithmic Solution, and Applications in Digital Pathology
Brendon Lutnick, Wen Dong, Zohar Nussinov +1
Unsupervised segmentation of large images using a Potts model Hamiltonian is unique in that segmentation is governed by a resolution parameter which scales the sensitivity to small…
Implicit Deep Latent Variable Models for Text Generation
Le Fang, Chunyuan Li, Jianfeng Gao +2
Deep latent variable models (LVM) such as variational auto-encoder (VAE) have recently played an important role in text generation. One key factor is the exploitation of smooth lat…