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
GlyphDiffusion: Text Generation as Image Generation—0
Reward Gaming in Conditional Text Generation—0
SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation—0
CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection—0
Technical Report: Auxiliary Tuning and its Application to Conditional Text Generation—0
Demonstrating EMMA: Embodied MultiModal Agent for Language-guided Action Execution in 3D Simulated Environments—0
TextGAIL: Generative Adversarial Imitation Learning for Text Generation—0
CtrlDiff: Boosting Large Diffusion Language Models with Dynamic Block Prediction and Controllable Generation—0
Bag-of-Vectors Autoencoders for Unsupervised Conditional Text Generation—0
Topic-Guided Variational Auto-Encoder for Text Generation—0
Topic-Guided Variational Autoencoders for Text Generation—0
Guided Generation of Cause and Effect—0
Hiring Now: A Skill-Aware Multi-Attention Model for Job Posting Generation—0
Improved Variational Neural Machine Translation by Promoting Mutual Information—0
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance—0
Input-length-shortening and text generation via attention values—0
Conditional Text Generation for Harmonious Human-Machine Interaction—0
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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