Conditional Text Generation
24 papers with code • 1 benchmarks • 4 datasets
The task of generating text according to some pre-specified conditioning (e.g. topic or sentiment or constraint)
Benchmarks
These leaderboards are used to track progress in Conditional Text Generation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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VitaminC
WikiGraphs
Lipogram-e
BalitaNLP
Most implemented papers
Pragmatically Informative Text Generation
sIncerass/prag_generation
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NAACL 2019
We improve the informativeness of models for conditional text generation using techniques from computational pragmatics.
Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation
morningmoni/ede
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EMNLP 2021
In this paper, we present a systematic analysis that studies whether current seq2seq models, especially pre-trained language models, are good enough for preserving important input concepts and to what extent explicitly guiding generation with the concepts as lexical constraints is beneficial.
GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation
beyondguo/genius
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We introduce GENIUS: a conditional text generation model using sketches as input, which can fill in the missing contexts for a given sketch (key information consisting of textual spans, phrases, or words, concatenated by mask tokens).
Generating Text through Adversarial Training using Skip-Thought Vectors
Attempts have been made to utilize GANs with word embeddings for text generation.
Encoder-Agnostic Adaptation for Conditional Language Generation
harvardnlp/encoder-agnostic-adaptation
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Large pretrained language models have changed the way researchers approach discriminative natural language understanding tasks, leading to the dominance of approaches that adapt a pretrained model for arbitrary downstream tasks.
Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders
WHUIR/PPVAE
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ACL 2020
Conditional Text Generation has drawn much attention as a topic of Natural Language Generation (NLG) which provides the possibility for humans to control the properties of generated contents.
ToTTo: A Controlled Table-To-Text Generation Dataset
We present ToTTo, an open-domain English table-to-text dataset with over 120, 000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.
Token Manipulation Generative Adversarial Network for Text Generation
MaskGAN opens the query for the conditional language model by filling in the blanks between the given tokens.
ETC-NLG: End-to-end Topic-Conditioned Natural Language Generation
gsarti/ETC-NLG
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We first test the effectiveness of our approach in a low-resource setting for Italian, evaluating the conditioning for both topic models and gold annotations.
Plug and Play Autoencoders for Conditional Text Generation
florianmai/emb2emb
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EMNLP 2020
Text autoencoders are commonly used for conditional generation tasks such as style transfer.
