Jul 6, 2024 · The DPPG-BART model has better long text generation capability compared to the GPT2-Small, GPT2-Large, BART and ProGen-2 modelling approaches.
Seq2Seq dynamic planning network for progressive text generation. https://doi ... Dyploc: Dynamic planning of content using mixed language models for text ...
We first propose a generalized decoding framework, ie, GSD, that can be used to uniformly describe and connect existing popular decoding methods.
DiffuSeq is a powerful model for text generation, matching or even surpassing competitive AR, iterative NAR, and large-PLMs on quality and diversity. Our study ...
Missing: dynamic network
PANET is proposed, a novel generation framework leveraging autoregressive self-attention mechanism to conduct content planning and surface realization ...
May 22, 2022 · Neural sequence-to-sequence (seq2seq) models are dominant methods for text generation nowadays, which are trained to maximize the log-likelihood.
We study the task of long-form opinion text generation, which faces at least two distinct challenges. First, existing neural generation.
Mar 17, 2022 · In this work, we propose PLANET, a novel text generation framework that dynamically per- forms content planning and surface realization in.
During text generation, the prior network first predicts a dis- crete code sequence given the input prompt, which is then applied to guide text generation. 2.1 ...
In this article, we give an overview of Natural Language Generation (nlg) from an applied system-building perspective. ... Progressive Generation of Long Text ...