Researchers developed ChatMPC, a simulation framework that translates natural language driving instructions into dynamic model predictive control parameters.
Fine-tuned BioBERT achieved a 97.03 F1-score extracting clinical entities from breast cancer summaries, though dosage and cancer stage remained more ...
Researchers evaluating robotic process automation discovery found that simple word-level text classifiers match complex neural representations while highlighting the generalization ...
A new unified framework from Leibniz University Hannover evaluates AI methods for revising inappropriate arguments, revealing that direct span-level editing ...
A scientific review published in BMC Artificial Intelligence evaluates how artificial intelligence, robotics, and natural language processing advance telemedicine and ...
A study of Swiss referendum debates reveals that large language models align with human evaluations of political arguments through surface ...
Researchers have introduced the Politus Dataset, combining social media data and privacy-preserving artificial intelligence to evaluate political public opinion and ...
A study shows that delaying conversation history compression until query time improves answer accuracy in long-running artificial intelligence dialogues.
Researchers developed and deployed a fine-grained natural language processing framework that accurately extracts context-aware medication details from unstructured Hungarian clinical ...
An empirical analysis of European social good initiatives reveals that while machine learning dominates classification tasks, foundational statistical methods remain ...
A joint deep learning framework called J-SUP unifies aspect-based sentiment analysis and consumer preference profiling within a shared Transformer architecture ...
A new study reports a quantum-inspired recommendation system combining fuzzy clustering, generative adversarial networks, and a dandelion-based optimizer that achieved ...
A multi-agent retrieval-augmented framework coordinates specialized language models to deliver structured, rubric-aligned feedback on student writing while restricting direct answer ...
Modeling text embeddings as cyclostationary sequences improves BERT-based multilingual sentiment analysis accuracy by up to 28% across five diverse datasets.
Researchers built a proof-of-concept framework that uses large language models to extract clinical entities from Thai medical documents and link ...
A dual-expert framework combining paraphrase-based augmentation and aspect tokenization reached 98.5% accuracy on the imbalanced Twitter US-Airline Sentiment dataset, outperforming ...
A new commentary shows that Latent Dirichlet Allocation, a natural language processing technique, can extract major themes from classical political ...
A paired analysis of the SMP2020-EWECT Weibo benchmark shows that during the COVID-19 outbreak the visible emotional structure of posts ...
A Frontiers in Health Services editorial argues that digital tools in care settings can either support person-centred practice or introduce ...
A Stanford analysis of more than 32,000 paired echocardiograms found that physicians typically report right ventricular systolic pressure changes only ...
