Latest Articles for Natural Language Processing

A new method to enhance relation extraction accuracy in large language models.

A new method combines logic and machine learning for better SQL queries.

This research presents a new method for LLMs to solve graph problems using code.

The study examines the effectiveness of specialized LLMs in clinical tasks.

This study evaluates how slight changes impact language model responses.

TAG improves how natural language questions are answered using databases.

Introducing an efficient method to fine-tune large language models dynamically.

A new method improves reasoning in large language models by addressing attestation bias.

A look into how RNNs interpret user requests and improve intent detection.

This study examines how LLMs process causality and their limitations.

This study examines the interaction of knowledge from LLMs and semantic towers.

Explore how dual encoders connect images to text.

A novel method accounts for human disagreement in natural language processing tasks.

This article examines the progress of vision-language models and their reasoning capabilities.

A deep dive into how next-token prediction shapes language understanding in models.

A look at the strengths and challenges of using COMET for machine translation assessment.

A new approach streamlines safety and helpfulness in language model training.

Discover efficient methods for fine-tuning large language models using Gaussian noise.

A new method to streamline language models while preserving their performance.

A new method focuses on relationships to enhance language model accuracy.

A look at LLM development and challenges for EU languages.

A look into Sparse Mamba, a method for better language model control.

Introducing a method that enhances model understanding of long texts.

A new algorithm improves dataset efficiency for fine-tuning language models.

RoAd offers an efficient method for fine-tuning large language models with fewer resources.

A new method locates video events using large pre-trained models without specific training.

Nexus combines efficiency, specialization, and adaptability in language model development.

LLaVA-MoD creates smaller multimodal models using knowledge from larger counterparts.

A new system enhances extractive summarization using Large Language Models.

A new method to assess and compare the knowledge of language models.

Efforts to create tools for processing the Sindhi language through large text data collection.

A method to speed up text generation without losing quality.

Introducing LRP4RAG, a method to better detect hallucinations in language models.

This paper presents a single-encoder model for improved image segmentation based on text descriptions.

MemLong improves language models' ability to handle lengthy texts effectively.

A look at how transfer learning impacts model performance through scaling laws.

A new method for extracting events from Portuguese narratives using advanced models.

ACE-2005-PT enhances event extraction capabilities for Portuguese language processing.

This work improves coreference resolution across languages with a new dataset and methods.

A new approach enhances video data handling while maintaining performance in real-time applications.