Latest Articles for Computational Linguistics

BatchBPE offers a faster approach to tokenization in natural language processing.

Study reveals how minor changes affect contextual word embeddings.

A new model improves Arabic NER using KNN search for better accuracy.

A novel approach merges multitask learning and generative adversarial networks for NLP tasks.

Exploring the challenges of prioritizing numbers over theoretical insights in linguistics research.

Research into Latin treebanks and morphological tagging enhances understanding of ancient texts.

Exploring how different tokenization strategies can enhance language model performance.

A new method boosts unidirectional models' performance in token classification tasks.

A method to improve how confident language models are in their text generation.

A new method improves language model capabilities without losing original knowledge.

Enhancing LLMs with external memory aids multi-step reasoning tasks.

New method enhances ASR accuracy using language models for better transcriptions.

A look at LLM development and challenges for EU languages.

Research on training language models for underrepresented languages efficiently.

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

A look into the effectiveness of pipeline versus end-to-end systems in summarizing across languages.

A novel approach aims to improve accuracy in language translation tasks.

RAG remains vital in optimizing language model responses, especially with long texts.

Two innovative methods enhance Chinese spelling correction performance and accuracy.

This article examines how derivation trees help classify languages as metalinear or regular.

A new model for better relation extraction using syntax and context.

Semformer integrates planning into language models, improving accuracy and efficiency.

Research focuses on improving language models' ability to understand longer texts.

New insights into how context and similarity affect language model performance.

A new method aims to reduce semantic leakage in cross-lingual sentence embeddings.

Examining the advantages of decoder-only models for machine translation tasks.

A method for training language models using focused data selection techniques.

A study on omissions and distortions in natural language generation from RDF data.

Examining the role of grammar books in translating low-resource languages.

A look into how word embeddings are analyzed using independent component analysis.

Discover how large language models improve argument analysis in texts.

Typos can greatly confuse advanced language models and affect their responses.

An overview of how language models learn and retain information.

Researchers investigate how large language models predict sequences using induction.

A new dataset for Kyrgyz word embeddings enhances language processing capabilities.

New models bring hope for Nepali natural language processing.

Creating a parser for Vietnamese using advanced models and improved resources.

This study explores how to compare sentence similarity across different languages.

Examining the effects of multimodal training on language skills in AI.

Examining the capabilities of large language models in planning tasks.