Latest Articles for Natural Language Processing

A new multilingual corpus improves argument generation and analysis.

This study highlights the importance of uncertainty in assessing Vision-Language Models.

KIEval offers interactive evaluation to address data contamination in language models.

This method enhances instruction data for multimodal tasks efficiently.

Combining big and small models boosts relation extraction effectiveness.

Explore the synergy of fuzzy and modal logic for decision-making in uncertain situations.

A new method enhances opinion summarization using domain knowledge in reward models.

Researchers investigate how models adapt when components are removed.

This work highlights dependencies between content and style in counterfactual generation.

ChunkAttention enhances self-attention for faster, more efficient language model performance.

This study presents a method to limit harmful outputs in large language models.

How the arrangement of examples shapes language model effectiveness.

This paper connects transformer models with Markov chains to enhance understanding.

This study examines how LLMs can effectively rank various entities based on different features.

A deep dive into methods for abusive language detection and text style transfer.

This article discusses a new framework for assessing hallucinations in LVLMs.

Exploring how quantum techniques can enhance natural language processing tasks.

SportQA evaluates language models' understanding of sports through over 70,000 questions.

Research highlights the bias in language model evaluations and proposes methods for improvement.

Analyzing the effects of reasoning methods on large language models' performance.

A new approach to improve knowledge distillation effectiveness using Sinkhorn distance.

Explore the data-centric approach to improving AI software systems.

A new method improves text generation speed using large and small language models.

A study on efficient methods for fine-tuning large models through Low-Rank Adaptation.

MobiLlama offers efficient language processing for devices with limited resources.

Research examines how LLMs connect information to answer complex questions.

Combining models improves sentiment analysis accuracy significantly.

A new method enhances speech recognition efficiency using low-rank adaptation.

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.