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 1–10 of 67 papers

TitleStatusHype
CtrlDiff: Boosting Large Diffusion Language Models with Dynamic Block Prediction and Controllable Generation—0
SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation—0
MOPO: Multi-Objective Prompt Optimization for Affective Text Generation—0
Discrete Copula Diffusion—0
Evaluation of Language Models in the Medical Context Under Resource-Constrained SettingsCode0
TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model EncodingsCode1
LOCOST: State-Space Models for Long Document Abstractive SummarizationCode1
Semantic Sensitivities and Inconsistent Predictions: Measuring the Fragility of NLI ModelsCode0
IPAD: Iterative, Parallel, and Diffusion-based Network for Scene Text RecognitionCode0
MEDITRON-70B: Scaling Medical Pretraining for Large Language ModelsCode4
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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