Latest Articles for Natural Language Processing

A robust Japanese corpus created from Common Crawl data improves LLM performance.

A new parser enhances language processing through brain-inspired methods.

Transforming an MCQA dataset for extractive questions in multiple languages.

Enhancing Japanese language models using English knowledge boosts performance significantly.

A new method enhances autoencoders for better data representation.

New module QASE improves accuracy in machine reading comprehension tasks.

Introducing the ViOCRVQA dataset for improved visual question answering in Vietnamese.

Researchers tackle spelling variations to improve NLP performance in Nigerian Pidgin.

Llip enhances how images are matched with diverse textual descriptions.

This research shows how LoRA improves language model performance on specific tasks.

A concise look at hallucinations in MLLMs and strategies to improve reliability.

A new benchmark assesses language models' understanding of linguistic competence.

An examination of how language models determine the truth of statements.

New metrics improve evaluation of information extraction systems in handwritten documents.

A study comparing Instance and Neuron Attribution methods in language models.

Study reveals insights on the balance between visual and textual inputs in VLMs.

Soft Preference Optimization improves how language models align with human preferences.

A framework to enhance reasoning accuracy in LLMs through structured verification.

Adapt-LLM improves LLM performance by balancing internal knowledge and external information.

A new model improves translation accuracy by predicting coreference features.

This framework improves how systems learn user likes through conversation.

A new method enhances reasoning in smaller language models for complex tasks.

A new method enhances reasoning in language models through effective preference learning.

Learn how RST-LoRA improves summarization using Rhetorical Structure Theory.

Learn how Context Steering enhances language model responses through adaptable context use.

This article examines biases and inconsistencies in LLM evaluations and suggests improvement methods.

A new method that balances privacy and text quality in language models.

A new approach enhances alignment of language models with human preferences.

An analysis of how Abstract Meaning Representation impacts LLM performance across various tasks.

This article explores in-context learning and its connection to information retrieval.

COPAL enhances language models for better adaptation without retraining.

Innovative method combines language models and human input for dialog datasets.

Recent research challenges the simplicity of the Knowledge Neuron Thesis in language models.

A new method enhances vision-language models without complex training.

Idefics2 showcases improvements in vision-language processing through innovative design choices.

Improving performance of open-source LLMs in converting plain language into SQL.

This method enhances language model fine-tuning using open, unlabeled datasets.

L3X aims to improve information extraction of long entity lists from extensive texts.

A new method enhances SQL query generation in ongoing conversations.

Exploring the intersection of quantum computing and language processing.