SOTAVerified

Conditional Text Generation

The task of generating text according to some pre-specified conditioning (e.g. topic or sentiment or constraint)

Papers

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Showing 51–67 of 67 papers

TitleStatusHype
TextGAIL: Generative Adversarial Imitation Learning for Text Generation—0
Topic-Guided Variational Auto-Encoder for Text Generation—0
Topic-Guided Variational Autoencoders for Text Generation—0
Transfer Reward Learning for Policy Gradient-Based Text Generation—0
WikiGraphs: A Wikipedia Text - Knowledge Graph Paired DatasetCode0
Pragmatically Informative Text GenerationCode0
Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-EncodersCode0
Exploring Conditional Text Generation for Aspect-Based Sentiment AnalysisCode0
Encoder-Agnostic Adaptation for Conditional Language GenerationCode0
Evaluation of Language Models in the Medical Context Under Resource-Constrained SettingsCode0
Token Manipulation Generative Adversarial Network for Text GenerationCode0
IPAD: Iterative, Parallel, and Diffusion-based Network for Scene Text RecognitionCode0
Generating Text through Adversarial Training using Skip-Thought VectorsCode0
EEL: Efficiently Encoding Lattices for RerankingCode0
Watermarking Conditional Text Generation for AI Detection: Unveiling Challenges and a Semantic-Aware Watermark RemedyCode0
ETC-NLG: End-to-end Topic-Conditioned Natural Language GenerationCode0
Semantic Sensitivities and Inconsistent Predictions: Measuring the Fragility of NLI ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-2-no-fine-tuningIgnored Constraint Error Rate28.2—Unverified
2GPT-2-fine-tuned-5-epochsIgnored Constraint Error Rate0.5—Unverified
3GPT-2-fine-tuned-20-epochsIgnored Constraint Error Rate0.3—Unverified
4GPT-2-with-filterIgnored Constraint Error Rate0—Unverified