Academic Articles & Research Papers

FREDC: A Few-Shot Relation Extraction Dataset for Chinese

Few-shot relation extraction (RE) is a critical task in natural language processing (NLP), yet benchmark datasets for non-English languages, particularly Chinese, remain scarce. Owing to their narrow focus and insufficient coverage of relat...

Enhancing educational semantic retrieval through dual objective fine tuning of open source embedding models

Abstract Recent advances in AI have catalyzed the adoption of intelligent educational tools, yet many semantic retrieval systems remain ill-suited to the unique linguistic and structural characteristics of academic content. This study prese...

Connectionist Approaches to Natural Language Processing

Preface, N. Sharkey and R. Reilly connectionist natural language processing semantics, M.D. Dyer, et al distributed symbol discovery through symbol recirculation - toward natural language processing in distributed connectionist networks, R....

GBsim: A Robust GCN-BERT Approach for Cross-Architecture Binary Code Similarity Analysis

Recent advances in graph neural networks have transformed structural pattern learning in domains ranging from social network analysis to biomolecular modeling. Nevertheless, practical deployments in mission-critical scenarios such as binary...

It-clefts as pragmatically-motivated extraposed constructions?

This paper investigates the discursive and pragmatic functions of it-clefts in contemporary English. The qualitative corpus-based study is based on the hypothesis that an it-cleft originates from the extraposition of a complex noun phrase i...

Deep Learning for Natural Language Processing

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

Abstract Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an ...

Graph-based Natural Language Processing and Information Retrieval

Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different p...

A broad-coverage natural language processing system.

Natural language processing systems (NLP) that extract clinical information from textual reports were shown to be effective for limited domains and for particular applications. Because an NLP system typically requires substantial resources ...

Neural transfer learning for natural language processing

The current generation of neural network-based natural language processing models excels at learning from large amounts of labelled data. Given these capabilities, natural language processing is increasingly applied to new tasks, new domain...

Fungi are overlooked dimethylsulfoniopropionate degraders in marine environments.

Deep learning for natural language processing: advantages and challenges

Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...

Natural Language Processing

ABSTRACT: Language is way of communicating your words Language helps in understanding the world,we get a better insight of the world. Language helps speakers to be as vague or as precise as they like. NLP Stands for natural language process...

Capire o interpretare (osservazioni su Celan)

La traduction de la poésie de Paul Celan pose la question et le défi de l’incommunicabilité, du moins au premier contact. Michele Ranchetti, qui a publié la traduction de deux recueils des poésies inédites Conseguito silenzio, et Sotto il t...

Specialized Large Language Model for Standardization of Locomotive Maintenance Data

Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data f...

Foundations of statistical natural language processing

Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains al...

Post-democratic discursive hegemony – a natural language processing-based analysis of Hungarian parliamentary discourses between 1998-2020

The parliament, as a key component of the public sphere, is both a reflection of and a stage for the post-democratic transition. Our study examines Hungarian parliamentary discourse as an indicator of a transition in which democratic instit...

Local, authentique, durable : la gastronomie entre ancrage territorial et dynamiques globales.

Since the early twenty-first century, ecological, economic, and geopolitical crises have intensified challenges related to food systems, reshaping dietary practices and individual relationships with the environment. Sustainable food consump...

Exploring Scientific Outputs about Globalization: A Conceptual Framework Study

IntroductionBibliometric analysis is widely acknowledged as a robust and systematic approach for examining extensive scholarly literature. It serves as a vital tool for mapping the landscape of contemporary research across various academic ...

Natural Language Processing for Requirements Engineering

Natural Language Processing for Requirements Engineering (NLP4RE) is an area of research and development that seeks to apply natural language processing (NLP) techniques, tools, and resources to the requirements engineering (RE) process, to...