Latest Articles for Language Processing

Strategies to enhance user trust during updates of language models.

PersonaRAG improves language models by personalizing responses based on user behavior.

This paper focuses on improving the reliability of language model outputs.

CEIPA helps uncover vulnerabilities in large language models to enhance their safety.

Exploring how AI can execute detailed spoken commands in virtual environments.

Exploring the complexities of transforming NFAs into DFAs in computer science.

A framework to create multilingual datasets for better AI understanding.

New tools for Arabic dialects improve banking communication and customer service.

Study analyzes text classification methods for subjective and objective content in five languages.

TokenSHAP reveals how words impact language model responses.

A new method to assess accuracy in language model outputs.

A method that translates plain language into executable programs for non-programmers.

An overview of NLG progress, challenges, and future research directions.

Examining the risks and safety measures for LLM-powered robots.

A new method promotes fairness in identifying targeted toxic language across demographic groups.

This study examines methods to distinguish between human-written and machine-generated text.

Examining the impact of LLMs on social stereotyping and ways to improve outcomes.

A new model to evaluate chance agreement in text annotation tasks.

A new method enhances watermarking without sacrificing text quality.

Exploring the role of domain-specific and uncertainty-aware models in healthcare.

Large language models streamline analysis of negotiation discussions, saving time and reducing errors.

Research presents a framework to reduce bias in AI-generated text.

A new model uses human memory principles to enhance language model performance.

A study highlights methods to find inaccuracies in German text generated by language models.

ZeroMMT uses monolingual multimodal data to enhance translation without expensive datasets.

Enhancing intent detection for Arabic-speaking customers in financial services.

Qalam offers improved recognition for Arabic text and handwriting.

A look at how open-source models measure up against commercial counterparts in biomedical tasks.

Examining issues with large language models in predicting missing list items.

New language-driven methods enhance robot learning for multiple tasks.

This study examines how context influences the meanings of polysemous words.

A new method enhances efficiency and quality in language model text generation.

A system that helps robots understand and follow verbal instructions for balance.

New methods improve speech systems for underrepresented languages.

A new framework enhances the process of verifying time-related claims online.

Improving trust and transparency in large language models through explainable AI.

A dataset featuring Ottoman Turkish and Russian texts for research enhancement.

Introducing DOPRA, a cost-effective way to improve MLLM accuracy.

Learn how cross-lingual entity alignment connects global information efficiently.

Our study targets regional identification of Italian tweets using language models.