Natural Language Processing

Published articles on text processing, computational linguistics, language models, and information extraction from OpenAlex.

Sample of the collection (25 of 132 items)

• Exploring the potential of using an AI language model for automated essay scoring Kansai University The widespread adoption of ChatGPT, an AI language model, has the potential to bring about significant changes to the research,…
• Artificial intelligence for cybersecurity: Literature review and future research directions Jožef Stefan Institute Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate repetitive tasks, accelerate threat…
• RoBERTa-LSTM: A Hybrid Model for Sentiment Analysis With Transformer and Recurrent Neural Network Multimedia University Due to the rapid development of technology, social media has become more and more common in human daily life. Social media is a platform…
• Roles and research foci of artificial intelligence in language education: an integrated bibliographic analysis and systematic review approach National Taiwan University of Science and Technology This study explores the roles and research foci of AILEd (Artificial Intelligence in Language Education). The AILEd studies published…
• Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition University of Science and Technology of China Linguistic knowledge is of great benefit to scene text recognition. However, how to effectively model linguistic rules in end-to-end…
• Automating creativity assessment with SemDis: An open platform for computing semantic distance Pennsylvania State University Creativity research requires assessing the quality of ideas and products. In practice, conducting creativity research often involves…
• Sentiment analysis on product reviews based on weighted word embeddings and deep neural networks Izmir Kâtip Çelebi University Summary Sentiment analysis is one of the major tasks of natural language processing, in which attitudes, thoughts, opinions, or…
• Emergent linguistic structure in artificial neural networks trained by self-supervision Stanford University This paper explores the knowledge of linguistic structure learned by large artificial neural networks, trained via self-supervision,…
• FineGym: A Hierarchical Video Dataset for Fine-Grained Action Understanding Chinese University of Hong Kong On public benchmarks, current action recognition techniques have achieved great success. However, when used in real-world applications,…
• Improving the translation of search strategies using the Polyglot Search Translator: a randomized controlled trial Bond University BACKGROUND: Searching for studies to include in a systematic review (SR) is a time- and labor-intensive process with searches of…
• Racial disparities in automated speech recognition Stanford University Automated speech recognition (ASR) systems, which use sophisticated machine-learning algorithms to convert spoken language to text, have…
• A Survey on Deep Learning for Named Entity Recognition Inception Institute of Artificial Intelligence Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types…
• Sentiment Analysis for E-Commerce Product Reviews in Chinese Based on Sentiment Lexicon and Deep Learning Changsha University of Science and Technology In recent years, with the rapid development of Internet technology, online shopping has become a mainstream way for users to purchase…
• What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis Jeonghun Baek et al. Many new proposals for scene text recognition (STR) models have been introduced in recent years. While each claim to have pushed the…
• VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research University of California, Santa Barbara We present a new large-scale multilingual video description dataset, VATEX <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"…
• Natural Questions: A Benchmark for Question Answering Research Google (United States) We present the Natural Questions corpus, a question answering data set. Questions consist of real anonymized, aggregated queries issued…
• Target-Dependent Sentiment Classification With BERT Chengdu University of Information Technology Research on machine assisted text analysis follows the rapid development of digital media, and sentiment analysis is among the prevalent…
• Measuring and Mitigating Unintended Bias in Text Classification Google (United States) We introduce and illustrate a new approach to measuring and mitigating unintended bias in machine learning models. Our definition of…
• SciTaiL: A Textual Entailment Dataset from Science Question Answering Allen Institute for Artificial Intelligence We present a new dataset and model for textual entailment, derived from treating multiple-choice question-answering as an entailment…
• DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding University of Technology Sydney Recurrent neural nets (RNN) and convolutional neural nets (CNN) are widely used on NLP tasks to capture the long-term and local…
• Reinforcement Learning for Relation Classification From Noisy Data Tsinghua University Existing relation classification methods that rely on distant supervision assume that a bag of sentences mentioning an entity pair are…
• Measuring Syntactic Complexity in L2 Writing Using Fine‐Grained Clausal and Phrasal Indices University of Hawaiʻi at Mānoa Abstract Syntactic complexity is an important measure of second language (L2) writing proficiency (Larsen–Freeman, 1978; Lu, 2011).…
• The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing Technion – Israel Institute of Technology Statistical significance testing is a standard statistical tool designed to ensure that experimental results are not coincidental. In…
• Dissecting Contextual Word Embeddings: Architecture and Representation Allen Institute for Artificial Intelligence Contextual word representations derived from pre-trained bidirectional language models (biLMs) have recently been shown to provide…
• Fully Character-Level Neural Machine Translation without Explicit Segmentation ETH Zurich Most existing machine translation systems operate at the level of words, relying on explicit segmentation to extract tokens. We…

Query this set from any AI agent

Agents: a markdown version of this page is at https://publicmcp.org/library/openalex-nlp.md.