Latest Articles for Natural Language Processing

Research on how inductive bias affects Transformer model performance.

Examining limitations of large vision-language models in detailed image understanding.

Research tackles timing issues in language model responses for improved accuracy.

This article explores optimization challenges in Transformers and the effectiveness of Adam over SGD.

GNER enhances entity recognition by integrating negative instances and improving context.

A new infrastructure connects NLP datasets to measure social intelligence.

A new method to evaluate the accuracy of LLM outputs using local intrinsic dimensions.

This survey reviews recent developments in multi-turn dialogue systems leveraging large language models.

A method to enhance accuracy in large language models while ensuring varied responses.

A new method enhances fine-tuning efficiency for language models across diverse tasks.

A study assessing various methods for interpreting language model neurons.

Researchers enhance Encoder-Decoder models to better predict sentence complexity using linguistic features.

Examining how models learn from multiple captions and the shortcuts they find.

Examining the impact of miscalibration on NLP models' resilience to adversarial attacks.

A dual method for training and using language models efficiently.

A new method helps robots learn tasks better using natural language guidance.

Examining self-attention and gradient descent in transformer models.

New method improves sentence embeddings using multiple prompts for better accuracy.

A look into how LLaMA-2 processes language using structured reasoning.

New dataset DANSK enhances Danish NER performance across various texts.

NeuroPrune shrinks language models while maintaining performance, making them faster and more accessible.

CLLMs enhance language generation speed and accuracy through refined training techniques.

A new ensemble approach improves parsing of complex sentence structures.

Examining the limitations of language models for generating planning definitions in diverse settings.

An analysis of Transformers and their in-context autoregressive learning methods.

TV-TREES improves video question answering with clear reasoning structures.

A new framework enhances multi-turn decision-making for language models.

Hawk and Griffin set a new standard in efficient language processing.

A high-quality dataset for training language models from English web content.

Learn how negative sampling improves the training of knowledge graph representation models.

TEncDM improves text generation quality through unique encoding techniques and self-conditioning.

Large language models face issues in accurately extracting relationships between entities.

DoCo enhances Large Visual-Language Models for better document comprehension.

A method for detecting shifts in word meanings across different eras.

TimeSET offers a fresh approach to organizing event timelines effectively.

MFS-HVE model enhances understanding of entity relationships using text and images.

Learn how eye tracking reveals reading habits and comprehension.

An overview of targeted sentiment analysis and its significance in news media.

A new method enhances model focus on important features during image classification.

This article explores attacks on LLMs and strategies for better protection.