Learning Videos and Geogebra: Do They Really Help Students Solve Their Answers? by Agustina Setyaningrum, Anton Jaelani

“…It turns out that videos are less able to help students complete their answers and GeoGebra can make students less than optimal in improving their thinking skills. …”
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MSAM：Video Question Answering Based on Multi-Stage Attention Model by LIANG Li-li, LIU Xin-yu, SUN Guang-lu, ZHU Su-xia

“…The video question answering (VideoQA) task requires understanding of semantic information of both the video and question to generate the answer.At present, it is difficult for VideoQA methods that are based on attention model to fully understand and accurately locate video information related to the question.To solve this problem, a multi-stage attention model network (MSAMN) is proposed. …”
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Elimination-based reasoning with LLM for multiple-choice educational question answering by Qianli Zhao, Mei Zhang

“…Abstract Large language models (LLMs) have made remarkable progress in question answering, but current approaches in the educational domain often directly predict an answer from multiple choices without thoroughly considering each option. …”
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Proteomics approaches – their potential for answering complex questions in meat science research by Elisabeth Huff-Lonergan, Steven M. Lonergan

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Peculiarities of cytokine type of regulation of immune answer in women with ovarian endometriomas by O. S. Shapoval, L. L. Vorontsova

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Informed-Learning-Guided Visual Question Answering Model of Crop Disease by Yunpeng Zhao, Shansong Wang, Qingtian Zeng, Weijian Ni, Hua Duan, Nengfu Xie, Fengjin Xiao

“…Consequently, research now focuses on training visual question answering (VQA) models. However, existing studies concentrate on identifying disease species rather than formulating questions that encompass crucial multiattributes. …”
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Accuracy of large language models for answering pediatric preventive dentistry questions by GUAN Boyan, XU Minghe, ZHANG Huiqi, MA Shulei, ZHANG Shanshan, ZHAO Junfeng

“…The average score of the ratings from 16 doctors was taken as the answer score. If the answer score was higher than 2.8, it was accepted as a accurate answer; if the score was lower than 1.4, it was accepted as an inaccurate answer; if the score was between 1.4 and 2.8, it was accepted as a partially accurate answer. …”
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Automatic question-answering modeling in English by integrating TF-IDF and segmentation algorithms by Hainan Wang

“…The results show that the proposed English automatic question-answering model has better accuracy and timeliness of answering questions, and the improved accuracy for weight calculation is better. …”
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Leveraging long context in retrieval augmented language models for medical question answering by Gongbo Zhang, Zihan Xu, Qiao Jin, Fangyi Chen, Yilu Fang, Yi Liu, Justin F. Rousseau, Ziyang Xu, Zhiyong Lu, Chunhua Weng, Yifan Peng

“…This method promises to improve the safety and reliability of LLMs deployed in healthcare domains by reducing the risk of misinformation, ensuring critical clinical content is retained in generated responses, and enabling more trustworthy use of LLMs in critical tasks such as medical question answering, clinical decision support, and patient-facing applications.…”
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Enhancing pre-trained language model by answering natural questions for event extraction by Yuxin Zhang, Qing Han

“…However, event extraction remains challenging due to the complexity and diversity of event expressions, as well as the ambiguity and context dependency of language.MethodsIn this paper, we propose a new method to improve the precision and recall of event extraction by including topic words related to events and their contexts, directing the model to focus on the relevant information, and filtering the noise.ResultsThis method was evaluated on the ACE 2005 dataset, achieving an F1-score of 77.27% with significant improvements in both precision and recall.DiscussionOur results show that the use of topic words and question answering techniques can effectively address the challenges faced by event extraction and pave the way for the development of more accurate and robust event extraction systems.…”
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ZPVQA: Visual Question Answering of Images Based on Zero-Shot Prompt Learning by Naihao Hu, Xiaodan Zhang, Qiyuan Zhang, Wei Huo, Shaojie You

“…The model devises a method of prompt learning by means of designed prompts that enable LLMs to generate caption prompts based on images and then combines the images with the generated caption prompts in order for the LLMs to generate questions and answers related to the images. In this study, we tested the performance of the ZPVQA model on multiple datasets, and achieve a performance improvement of 3.4% on the VQAv2 dataset and 2.6% on the OK-VQA dataset. …”
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Essay Answer Detection System Uses Cosine Similarity and Similarity Scoring in Sentences by Siti Yuliyanti, Diah Hidayatul Ula

“…So this research carried out the development of an application with an automatic answer correction model with cosine similarity to measure how similar or how far two vectors are in multidimensional space. …”
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Alternative Approaches in Evaluating the EU SME Policy: Answers to the Question of Impact and Legitimization by Robert K. Gruenwald

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Effects of the question-and-answer relationship strategy on students’ reading comprehension and critical thinking by Tsegaye Girma, Marew Alemu, Sefa Meka

“… This research aimed to determine whether the Question-and-Answer Relationship (QAR) strategy can improve students’ reading comprehension of narrative texts and critical thinking skills in Amharic. …”
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Effects of the question-and-answer relationship strategy on students’ reading comprehension and critical thinking by Tsegaye Girma, Marew Alemu, Sefa Meka

“… This research aimed to determine whether the Question-and-Answer Relationship (QAR) strategy can improve students’ reading comprehension of narrative texts and critical thinking skills in Amharic. …”
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Effects of the question-and-answer relationship strategy on students’ reading comprehension and critical thinking by Tsegaye Girma, Marew Alemu, Sefa Meka

“… This research aimed to determine whether the Question-and-Answer Relationship (QAR) strategy can improve students’ reading comprehension of narrative texts and critical thinking skills in Amharic. …”
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Research on intelligent government question answering system with autonomous learning and memory function by Fang Haiquan, Deng Mingming

“…After computer experiments, it has been proven that the proposed method can achieve automatic real-time updates of the knowledge base, and the constructed question answering system has autonomous learning and memory functions, improving the intelligence level of the task-based question answering system.…”
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Extracellular vesicles in cancer´s communication: messages we can read and how to answer by Alena Semeradtova, Michaela Liegertova, Regina Herma, Magdalena Capkova, Chiara Brignole, Genny Del Zotto

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Dataset for legal question answering system in the Indian judiciary contextMendeley Data by Veningston K, Apratim Mishra

“…Cosine similarity measures how well the model captures the nuances of legal language between actual and generated answers. This ensures the dataset is well-suited for real-world legal applications, making it a valuable resource for improving AI-driven legal information retrieval systems.…”
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TQAgent: Enhancing Table-Based Question Answering with Knowledge Graphs and Tree-Structured Reasoning by Jianbin Zhao, Pengfei Zhang, Yuzhen Wang, Rui Xin, Xiuyuan Lu, Ripeng Li, Shuai Lyu, Zhonghong Ou, Meina Song

“…Table-based question answering (TableQA) has emerged as an important task in natural language processing, yet existing models face challenges in handling complex reasoning and mitigating hallucinations, especially when dealing with diverse table structures. …”
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