Results 101 to 110 of about 1,006,138 (295)

Enriching Portuguese Word Embeddings with Visual Information

, 2022
This work focuses on the enrichment of existing Portuguese word embeddings with visual information in the form of visual embeddings. This information was extracted from images portraying given vocabulary terms and imagined visual embeddings learned for ...
Bernardo Scapini Consoli, Renata Vieira, Consoli, Bernardo, Vieira, Renata   +3 more
core   +1 more source

Artificial Intelligence‐Driven Extraction of Patient‐Reported Pain Outcomes in Osteoarthritis Using Large Language Models

Arthritis Care &Research, Accepted Article.
Objective Patient‐reported outcome measures (PROMs) are central to assessing symptom burden and treatment response in Osteoarthritis (OA) but are often embedded in unstructured clinical notes. We evaluated whether prompt‐engineered large language models (LLMs) could accurately extract or infer pain scores on a 0‐10 scale from routine OA clinical ...
Jainesh Doshi, Stephen Batter, Yiyuan Wu, William Salerno, Alice Santilli, Sandhya Kannayiram, Susan Goodman, Bella Mehta   +7 more
wiley   +1 more source

Event-Driven Semantic Service Discovery Based on Word Embeddings

IEEE Access, 2018
Service discovery is vital to event handling in Internet of Things applications which are based on the event-driven service-oriented architecture. However, in service discovery, the problem of service matching that establishes relationships between ...
Fagui Liu, Dacheng Deng, Jun Jiang, Quan Tang   +3 more
doaj   +1 more source

Emotional Embeddings: Refining Word Embeddings to Capture Emotional Content of Words

CoRR, 2019
Word embeddings are one of the most useful tools in any modern natural language processing expert's toolkit. They contain various types of information about each word which makes them the best way to represent the terms in any NLP task. But there are some types of information that cannot be learned by these models.
Armin Seyeditabari, Narges Tabari, Shafie Gholizadeh, Wlodek Zadrozny   +3 more
openaire   +3 more sources

Biodegradable and Biocompatible Functional Polymers for Biomedical Applications

Advanced Functional Materials, EarlyView.
Biodegradable and biocompatible functional polymers integrate electrical, mechanical, and stimuli‐responsive functionalities while enabling programmed degradation under physiological conditions. This review introduces recent advances in conductive, shape‐memory, self‐healing, photocurable, and adhesive polymer systems, emphasizing material design ...
Won Bae Han, Shuvra Mondal, Sungkeun Han, Chan‐Hwi Eom, Venkata Ramesh Naganaboina, Suk‐Won Hwang   +5 more
wiley   +1 more source

Investigating Word Meta-Embeddings by Disentangling Common and Individual Information

IEEE Access, 2020
In the field of natural language processing, combining multiple pre-trained word embeddings has become a viable approach to improve word representations. However, there is still a lack of understanding of why such improvements can be achieved.
Wenfan Chen, Mengmeng Sheng, Jiafa Mao, Weiguo Sheng   +3 more
doaj   +1 more source

Distilling Word Embeddings

Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, 2016
Distilling knowledge from a well-trained cumbersome network to a small one has recently become a new research topic, as lightweight neural networks with high performance are particularly in need in various resource-restricted systems. This paper addresses the problem of distilling word embeddings for NLP tasks.
Lili Mou, Ran Jia, Yan Xu 0013, Ge Li 0001, Lu Zhang 0023, Zhi Jin 0001   +5 more
openaire   +2 more sources

Better Word Embeddings by Disentangling Contextual n-Gram Information [PDF]

, 2019
Pre-trained word vectors are ubiquitous in Natural Language Processing applications. In this paper, we show how training word embeddings jointly with bigram and even trigram embeddings, results in improved unigram embeddings.
Pagliardini, Matteo, Gupta, Prakhar, Matteo Pagliardini, Prakhar Gupta, Martin Jaggi, Jaggi, Martin   +5 more
core   +1 more source

An Edible Chitosan‐Based Acoustic Sensor for Sound‐Responsive Actuation in Edible Robots

Advanced Functional Materials, EarlyView.
This study introduces an edible acoustic sensor for robotic food and edible robotics. Built from a chitosan piezoelectric film between gold electrodes, the sensor enables acoustic communication through ON/OFF keying. Integrated into an edible robot with pneumatically actuated arms and neck, it responds to high‐frequency tones.
Valerio Francesco Annese, Bokeon Kwak, Gaia de Marzo, Giulia Coco, Valentina Antonaci, Leonardo Lamanna, Massimo De Vittorio, Dario Floreano, Mario Caironi   +8 more
wiley   +1 more source

A Correlated Topic Model Using Word Embeddings

, 2017
Conventional correlated topic models are able to capture correlation structure among latent topics by replacing the Dirichlet prior with the logistic normal distribution.
Jing Gao, Wayne Xin Zhao, Guangxu Xun, Yaliang Li, Aidong Zhang   +4 more
core   +1 more source