Latest Articles for Text Generation

A new method for creating engaging informal summaries using offline reinforcement learning.

Introducing a detailed approach to assess machine-generated text quality.

Discover TESGAN, a novel framework for more unique text synthesis.

A fresh approach to assess the quality of generated text in large language models.

Introducing NADO as an effective method for controlled text generation.

ZeroGen generates text using both visual and textual inputs efficiently.

A study on assessing text generation quality from large language models.

A new method for faster text generation through efficient early exits in language models.

A look at how to identify and fix false information in AI text generation.

This study examines how language models generate text from knowledge graphs.

Introducing a framework for advanced text generation using language models.

New methods improve watermarking in AI-generated text without sacrificing quality.

This study shows how appraisal theories enhance emotional text generation in natural language processing.

A method to embed reliable watermarks in generated text to trace its origin.

New method improves identification of AI-generated text.

Introducing a secure method to identify machine-generated text.

A new method improves text creation reflecting specific emotions efficiently.

A new method enhances the accuracy of text generated from knowledge graphs.

Introducing a flexible platform for fine-grained text evaluations.

A novel approach reduces harmful text generation in large language models.

A method to enhance language models' performance on lengthy text generation.

A new method quantifies confidence in language model answers for better reliability.

Learn how embedding space affects text accuracy in large language models.

Quantum techniques are transforming generative models for data generation.

Research shows counterfactuals can improve smaller language model performance and calibration.

A look at how Contrastive Decoding improves reasoning in language models.

New methods improve text generation quality and efficiency in artificial intelligence.

New methods improve style transfer for text while maintaining meaning.

Introducing Regular Expression Instruction for flexible controlled text generation.

A new approach to identify deepfake texts using advanced machine learning techniques.

A new approach enhances text generation by focusing on harmful patterns.

A new method combines PPO and MCTS for improved text generation.

Discover how the JAM framework combines text and images for improved content creation.

Exploring a new tool for better text generation control.

New model generates text using pixel representations, improving clarity and performance.

Examining the nature and capabilities of language models in generating meaningful text.

A look at how LLMs enhance NLG evaluation methods.

MuMo speeds up language model performance for non-Roman scripts.

A new approach improves language model outputs based on human feedback.

This paper examines the effectiveness of AI-generated text versus human-written content.