Question Dependent Recurrent Entity Network for Question Answering by Andrea Madotto, Giuseppe Attardi

“…Question Answering is a task which requires building models capable of providing answers to questions expressed in human language. …”
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Enhancing Visual Question Answering for Multiple Choice Questions by Rashi Goel, Harsh Nandwani, Eshaan Shah, Ashalatha Nayak, Archana Praveen Kumar

“…Using MCQs provides the model with some context of the correct answer, improving its performance over a simple multiclass classification task. …”
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A topic-enhanced python question-answering model by WANG Shuo, LIU Xin, LU Xuesong

“…With the development of large language model technology, the application of retrieval enhancement in the field of education has become one of the hot research directions, with the aim of alleviating the hallucination problem of large language models and improving the accuracy of large language models in answering educational questions. …”
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A topic-enhanced python question-answering model by WANG Shuo, LIU Xin, LU Xuesong

“…With the development of large language model technology, the application of retrieval enhancement in the field of education has become one of the hot research directions, with the aim of alleviating the hallucination problem of large language models and improving the accuracy of large language models in answering educational questions. …”
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Design: the answer of contemporary businesses to the requirements of sustainable development by Rodica Pamfilie, Roxana Procopie, Magdalena Bobe, Smaranda Vişan, Robert Bumbac

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STRIVING FOR QUALITY - THE ANSWER OF HISTORY (AN EXAMPLE OF HOSPITAL SECTOR) by Darina Mineva

“…The internal motivation of the owners of the means of production increases with a motive for profit, at the expense of the external goal - the duty to society: paying taxes, improving the quality of life and securing salaries. …”
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Advancing medical question answering with a knowledge embedding transformer. by Xiang Zhu, Mustaqeem Khan, Abdelmalik Taleb-Ahmed, Alice Othmani

“…The results demonstrate the system's ability to deliver accurate and ethical answers. This integrated method improves response speed and quality. …”
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Deep Memory Fusion Model for Long Video Question Answering by SUN Guanglu, WU Meng, QIU Jing, LIANG Lili

“…Long video question answering contains rich multimodal semantic information and inference information. …”
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Recent Developments to the ANSWERS® Monte Carlo Codes MONK® and MCBEND® by Fildes Jessica, Richards Simon, Bird Adam, Cox Andrew, Fry Timothy, Hanlon David, Jones Brian, Long David, Tantillo Francesco, Wright George, Hiles Richard

“…MONK® and MCBEND® are two advanced Monte Carlo codes developed by the ANSWERS® Software Service, which have been used in over 30 countries worldwide for a range of applications, and have been well-established in the UK criticality and shielding communities respectively over the course of several decades. …”
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Visual Question Answering in Robotic Surgery: A Comprehensive Review by Di Ding, Tianliang Yao, Rong Luo, Xusen Sun

“…Visual Question Answering (VQA) in robotic surgery is rapidly becoming a pivotal technology in medical AI, addressing the complex challenge of interpreting multimodal surgical data to support real-time decision-making. …”
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TSQ: An Optimized Framework for Efficiently Answering Time Series Queries by Feifan Pu, Jianqiu Xu

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Medical Knowledge-Based Differential Image Visual Question Answering by Fangpeng Lu, Songyan Liu, Wenbin Lu, Peng Chen, Boyang Ding

“…Experimental results demonstrate that our method significantly enhances the performance of the differential medical visual question answering task. This advancement is of considerable reference value in improving the applicability and interpretability of medical visual question answering.…”
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Question Answering System for Applicant Support by Using Modern Messengers by Dmitry R. Filonov, Dmitry Ju. Chalyy, Dmitry M. Murin, Valery G. Durnev, Valery A. Sokolov

“…In this paper, we consider a specialized question answering system that uses today’s messaging services infrastructure to support university applicants. …”
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Solving Linear Programming Problems by Reducing to the Form with an Obvious Answer by Gleb D. Stepanov

“…The method is obtained by improving the classical simplex method, which when involving geometric considerations, in fact, generalizes the Gauss complete exclusion method for solving systems of equations. …”
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ReceiptQA: A Question-Answering Dataset for Receipt Understanding by Mahmoud Abdalla, Mahmoud SalahEldin Kasem, Mohamed Mahmoud, Bilel Yagoub, Mostafa Farouk Senussi, Abdelrahman Abdallah, Seung Hun Kang, Hyun Soo Kang

“…In this paper, we introduce <span style="font-variant: small-caps;">ReceiptQA</span>, a novel large-scale dataset designed for receipt understanding through question-answering (QA). <span style="font-variant: small-caps;">ReceiptQA</span> contains 171,000 question–answer pairs derived from 3500 receipt images, constructed via two complementary methodologies: (1) LLM-Generated Dataset: 70,000 synthetically generated QA pairs, where each receipt is paired with 20 unique, context-specific questions. …”
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Is it a pediatric orthopaedic urgency or not? Can ChatGPT answer this question? by Sema Ertan Birsel, Onur Oto, Baris Görgün, İrem Hazal İnan, Ali Şeker, Muharrem İnan

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Hierarchical Modeling for Medical Visual Question Answering with Cross-Attention Fusion by Junkai Zhang, Bin Li, Shoujun Zhou

“…Experiments on the Rad-Restruct benchmark demonstrate that the HiCA-VQA framework outperforms existing state-of-the-art methods in answering hierarchical fine-grained questions, especially achieving an 18 percent improvement in the F1 score. …”
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Unsupervised Context-Linking Retriever for Question Answering on Long Narrative Books by Mohammad A. Ateeq, Sabrina Tiun, Hamed Abdelhaq, Wandeep Kaur

“…This method optimizes the retriever to identify passages with sufficient context to accurately reconstruct both the question and the answer, improving retrieval accuracy. UCLR also identifies key events surrounding each passage in the retrieved set and constructs a new set of passages from these key events, enabling coverage of both broader narrative structures and finer details. …”
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Weapon equipment question answering system based on BERT and knowledge graph by WANG Bo, JIANG Xuping, HUANG Qihong

“…The system achieves named entity recognition and classification of questions by fine-tuning the BERT model; it generates graph database query statements by filling named entities into question templates and generates answers by filling answer templates. Analysis of test results shows that this system is capable of effectively ranking correct answers at the top and has achieved a good balance between accuracy and comprehensiveness, although there is still room for improvement.…”
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Evaluating search engines and large language models for answering health questions by Marcos Fernández-Pichel, Juan C. Pichel, David E. Losada

“…Abstract Search engines (SEs) have traditionally been primary tools for information seeking, but the new large language models (LLMs) are emerging as powerful alternatives, particularly for question-answering tasks. This study compares the performance of four popular SEs, seven LLMs, and retrieval-augmented (RAG) variants in answering 150 health-related questions from the TREC Health Misinformation (HM) Track. …”
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