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Research paper

A Comparative Study of Qwen and Gemma Large Language Models for Social Media Slang and Emoji Sentiment Analysis for Business Recommender Systems

Research paper by Konstantinos I. Roumeliotis and collaborators, published 2026 in International Conference on Information, Intelligence, Systems & Applications (IISA). Research area: Sentiment Analysis and Opinion Mining.

Konstantinos I. Roumeliotis, Dionisis Margaris, Dimitris Spiliotopoulos, Giorgos Mpardis, Christos Tryfonopoulos, Costas Vassilakis
Not specifiedView resource
Research paper

A Scoping Review of Artificial Intelligence–Generated Image-Based Sexual Abuse: Terminology, Nature, Prevalence, Attitudes, and Harms (In Press)

Artificial intelligence–generated image-based sexual abuse (AI-IBSA), colloquially known as “sexual deepfakes”, includes the non-consensual creation and/or sharing of intimate images generated by and/or modified using artificial intelligence (“AI-IBSA content”). While literature on AI-IBSA is growing, a scoping review of empirical (scholarly and gray) literature on the terminology, nature, prevalence (victimization and perpetration), community attitudes toward, and harms and impacts of AI-IBSA by and/or against adults is yet to be undertaken through a gender-inclusive lens. Thus, we searched six bibliographic databases to identify studies tha

Alice Witt, Gemma Stevens, Alexa Ridgway, Adrienne Ringin
Creative Commons Attribution Non Commercial 4.0 InternationalView resource
Research paper

Additional file 1 of Flow starvation during square-flow assisted ventilation detected by supervised deep learning techniques

Additional file 1. Supplementary materials, tables and figures.

de Haro, Candelaria, Santos-Pulpón, Verónica, Telías, Irene, Xifra-Porxas, Alba, Subirà, Carles, Batlle, Montserrat, Fernández, Rafael, Murias, Gastón, Albaiceta, Guillermo M., Fernández-Gonzalo, Sol, Godoy-González, Marta, Gomà, Gemma, Nogales, Sara, Roca, Oriol, Pham, Tai, López-Aguilar, Josefina, Magrans, Rudys, Brochard, Laurent, Blanch, Lluís, Sarlabous, Leonardo
Creative Commons Attribution 4.0 InternationalView resource
Research paper

Advancing Prompt Recovery in NLP: A Deep Dive into the Integration of Gemma-2b-it and Phi2 Models

Prompt recovery, a crucial task in natural language processing, entails the reconstruction of prompts or instructions that language models use to convert input text into a specific output. Although pivotal, the design and effectiveness of prompts represent a challenging and relatively untapped field within NLP research. This paper delves into an exhaustive investigation of prompt recovery methodologies, employing a spectrum of pre-trained language models and strategies. Our study is a comparative analysis aimed at gauging the efficacy of various models on a benchmark dataset, with the goal of pinpointing the most proficient approach for promp

Chen, Jianlong, Xu, Wei, Ding, Zhicheng, Xu, Jinxin, Yan, Hao, Zhang, Xinyu
arXiv.org perpetual, non-exclusive licenseView resource

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