Results 91 to 100 of about 302,572 (324)

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

NLP-ADBench: NLP Anomaly Detection Benchmark

Findings of the Association for Computational Linguistics: EMNLP 2025
Anomaly detection (AD) is an important machine learning task with applications in fraud detection, content moderation, and user behavior analysis. However, AD is relatively understudied in a natural language processing (NLP) context, limiting its effectiveness in detecting harmful content, phishing attempts, and spam reviews.
Li, Yuangang, Li, Jiaqi, Xiao, Zhuo, Yang, Tiankai, Nian, Yi, Hu, Xiyang, Zhao, Yue   +6 more
openaire   +2 more sources

TectoMT: Modular NLP Framework [PDF]

, 2010
In the present paper we describe TectoMT, a multi-purpose open-source NLP framework. It allows for fast and efficient development of NLP applications by exploiting a wide range of software modules already integrated in TectoMT, such as tools for sentence segmentation, tokenization, morphological analysis, POS tagging, shallow and deep syntax parsing ...
Popel M., Zabokrtsky Z.
openaire   +2 more sources

BOOSTING ESL, SPEAKING AND VOCABULARY SKILLS WITH NLP: PRACTICAL TOOLS FOR THE MODERN CLASSROOM [PDF]

Езиков свят
Every learner encounters difficulties expressing their thoughts clearly, particularly those acquiring English as a second language. This study investigates the effect of Natural Language Processing (NLP) anchoring techniques on specific speaking sub ...
Doliana CELAJ, Greta JANI
doaj   +1 more source

Quantifying Uncertainties in Natural Language Processing Tasks

, 2018
Reliable uncertainty quantification is a first step towards building explainable, transparent, and accountable artificial intelligent systems. Recent progress in Bayesian deep learning has made such quantification realizable.
Wang, William Yang, Xiao, Yijun
core   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Automatic Identification of Narratives: Evaluation Framework, Annotation Methodology, and Dataset Creation

IEEE Access
One of the fundamental components of understanding online discourse in social networks is the identification of narratives. For example, the analysis of disinformation campaigns requires some inference about their communication goals that, in turn ...
Jesus M. Fraile-Hernandez, Anselmo Penas, Pablo Moral   +2 more
doaj   +1 more source

An XML-based Tool for Tracking English Inclusions in German Text [PDF]

, 2004
The use of lexicons and corpora advances both linguistic research and performances of current natural language processing (NLP) systems. We present a tool that exploits such resources, specifically English and German lexical databases and the World Wide ...
Alex, Beatrice, Grover, Claire
core   +1 more source

Artificial Intelligence Powers Protein Functional Annotation

Advanced Science, EarlyView.
This review systematically summarizes how artificial intelligence advances protein functional annotation. It organizes existing methods into six unified modeling paradigms and analyzes their applications in Gene Ontology and Enzyme Commission prediction.
Wenkang Wang, Qiurong Yang, Min Zeng, Ruiqing Zheng, Min Li   +4 more
wiley   +1 more source

OsGSK2‐OsTCP19 Module Integrates Nitrogen and Brassinosteroid Signaling to Regulate Nitrogen Utilization and Root Growth in Rice

Advanced Science, EarlyView.
OsGSK2‐OsTCP19 module regulating nitrate response and lateral root (LR) development. Low‐nitrate condition results in reduced BR response, accumulation of OsGSK2 and phosphorylated OsTCP19, which suppresses the expression of nitrate‐responsive genes and LR‐development genes and impairs rice growth.
Yongqiang Liu, Weiwei Li, Xiaohui Ma, Xiaohan Wang, Yarong Shi, Xiahe Huang, Xinran Li, Yingchun Wang, Hongning Tong, Bin Hu, Wenbin Zhou, Chengcai Chu   +11 more
wiley   +1 more source