Methods › General › Fine-Tuning › ERNIE-GEN
ERNIE-GEN
Introduced by Dongling Xiao et al. in ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
ERNIE-GEN is a multi-flow sequence to sequence pre-training and fine-tuning framework which bridges the discrepancy between training and inference with an infilling generation mechanism and a noise-aware generation method. To make generation closer to human writing patterns, this framework introduces a span-by-span generation flow that trains the model to predict semantically-complete spans consecutively rather than predicting word by word. Unlike existing pre-training methods, ERNIE-GEN incorporates multi-granularity target sampling to construct pre-training data, which enhances the correlation between encoder and decoder.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation 26 Jan 2020 · 5 repositories · arXiv:2001.11314
Tasks archive 2025-07-28
8 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Abstractive Text Summarization | 1 |
| Decoder | 1 |
| Dialogue Generation | 1 |
| Generative Question Answering | 1 |
| Question Generation | 1 |
| Question-Generation | 1 |
| Text Generation | 1 |
| Text Summarization | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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