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Journal articles on the topic 'Understanding of the text'

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1

Rasuljonova, Rasuljonova Saida. "UNDERSTANDING UZBEK TEXTS IN ENGLISH." Journal of Science-Innovative Research in Uzbekistan 2, no. 10 (2024): 318–21. https://doi.org/10.5281/zenodo.13941392.

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In this article includes it should be said that communication between people is carried out through the means of communication texts (and this is recognized by the creators of text linguistics, in general, by the majority of text researchers), limiting the text only to the written form contradicts the existing rules of text theory. After all, it is impossible to imagine that any communication between people takes place only and only in written form.
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Hiebert, Elfrieda H., and P. David Pearson. "Understanding Text Complexity." Elementary School Journal 115, no. 2 (2014): 153–60. http://dx.doi.org/10.1086/678446.

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Goldman, Robert P., and Eugene Charniak. "Probabilistic text understanding." Statistics and Computing 2, no. 2 (1992): 105–14. http://dx.doi.org/10.1007/bf01889589.

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El-Gamal, S. S., and M. M. Esmail. "Understanding clinical narrative text." Medical Informatics 20, no. 2 (1995): 161–73. http://dx.doi.org/10.3109/14639239509025354.

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5

Gerrig, Richard J. "Models of understanding text." Journal of Pragmatics 30, no. 5 (1998): 637–45. http://dx.doi.org/10.1016/s0378-2166(98)00038-1.

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6

Banik, Dr Somdev. "Understanding The Fear of the Text in a Post." Indian Journal of Applied Research 3, no. 4 (2011): 225–26. http://dx.doi.org/10.15373/2249555x/apr2013/75.

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7

Ivgi, Maor, Uri Shaham, and Jonathan Berant. "Efficient Long-Text Understanding with Short-Text Models." Transactions of the Association for Computational Linguistics 11 (2023): 284–99. http://dx.doi.org/10.1162/tacl_a_00547.

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Abstract Transformer-based pretrained language models (LMs) are ubiquitous across natural language understanding, but cannot be applied to long sequences such as stories, scientific articles, and long documents due to their quadratic complexity. While a myriad of efficient transformer variants have been proposed, they are typically based on custom implementations that require expensive pretraining from scratch. In this work, we propose SLED: SLiding-Encoder and Decoder, a simple approach for processing long sequences that re-uses and leverages battle-tested short-text pretrained LMs. Specifica
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8

D.Umanandhini*1, &. S.Manimegalai2. "FUZZY SCORE BASED SHORT TEXT UNDERSTANDING FROM CORPUS DATA USING SEMANTIC DISCOVERY." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 12 (2017): 268–73. https://doi.org/10.5281/zenodo.1116682.

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Short text understanding and short text are always more ambiguous. These short texts are produced including Search queries, Tags, Keywords, Conversation or Social posts and containing limited context. Generally short texts do not contain sufficient collection of data to support many state-of-the-art approaches for text mining such as topic modelling. It presents a comprehensive overview of short text understanding. Here we used a novel framework are Text Feature Extraction Algorithm and Fuzzy weighted Vote algorithm First, Text classification based on semantic feature extraction.   Its go
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9

Pulles, Maaike, Jan Berenst, Tom Koole, and Kees de Glopper. "Text formulations as practices of demonstrating understanding in dialogic reading." Text & Talk 41, no. 4 (2021): 515–38. http://dx.doi.org/10.1515/text-2019-0222.

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Abstract This paper examines text formulations in the interaction between peers in primary school during dialogic reading, in inquiry learning settings. In this context pupils collaboratively use information from texts to answer their research questions. The data analyzed include 25 excerpts of pupils demonstrating understanding of text. We used Conversation Analysis to analyze how pupils demonstrate their understanding by the use of text formulations, as a specific type of formulations, and how these formulations function as a bridge between the reading action and the discussion of text conte
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Kravchyna, Tetiana. "MODELS OF FOREIGN TEXT UNDERSTANDING." Scientific Notes of Ostroh Academy National University: Psychology Series 1, no. 15 (2022): 14–18. http://dx.doi.org/10.25264/2415-7384-2022-15-14-18.

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The article aims: 1) to analyze the theoretical development of models for understanding a foreign language text from a psychological point of view; 2) to emphasize their contribution to the general theory of understanding; 3) to structure, single out models of comprehension of a foreign language text. It also considers psycholinguistic and cognitive processes that affect the reader’s understanding of a foreign language text, analyzes resonant, constructivist and dynamic approaches to the processes of decoding lexical and grammatical information and inference of the meaning of the text. The mai
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Feshchenko, Vladimir V. "Understanding and misunderstanding absurdist text." Sibirskiy filologicheskiy zhurnal, no. 4 (December 1, 2009): 102–9. http://dx.doi.org/10.17223/18137083/29/14.

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12

Gibbs, Raymond W. "Authorial Intentions in Text Understanding." Discourse Processes 32, no. 1 (2001): 73–80. http://dx.doi.org/10.1207/s15326950dp3201_04.

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13

Allbritton, David W., and Richard J. Gerrig. "Participatory responses in text understanding." Journal of Memory and Language 30, no. 5 (1991): 603–26. http://dx.doi.org/10.1016/0749-596x(91)90028-i.

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14

Palmer, Martha S., Rebecca J. Passonneau, Carl Weir, and Tim Finin. "The KERNEL text understanding system." Artificial Intelligence 63, no. 1-2 (1993): 17–68. http://dx.doi.org/10.1016/0004-3702(93)90014-3.

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15

Li, Jun, Guimin Huang, Jianheng Chen, and Yabing Wang. "Short Text Understanding Combining Text Conceptualization and Transformer Embedding." IEEE Access 7 (2019): 122183–91. http://dx.doi.org/10.1109/access.2019.2938303.

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Rohmansyah, Rohmansyah. "Understanding of Polygamy in the Qur’anic Text, Hadith Text, and Biblical Text." Al-Ihkam: Jurnal Hukum & Pranata Sosial 14, no. 2 (2020): 317. http://dx.doi.org/10.19105/al-lhkam.v14i2.2529.

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17

Hapipi, Syahrul Azmi, and Wahidaturrahmi. "Mathematics Students’ Ability in Understanding Text." Journal of Educational and Social Research 11, no. 3 (2021): 71. http://dx.doi.org/10.36941/jesr-2021-0052.

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This study aims to obtain a description of the students’ ability in understanding text. To achieve the objective, the study selected 216 mathematics students in a proportionate stratified random sampling. The students were asked to answer questions from a text that was designed and validated by a linguist. The samples were asked to fill out a questionnaire. The results show that there was a relationship between the length of studying mathematics (semester level) and the student’s ability to understand the idea of a text, the ability to determine conclusions from the given text, and the student
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18

Sugeno, Michio. "Text Understanding in Brain-Style Computing." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 17, no. 1 (2005): 19–28. http://dx.doi.org/10.3156/jsoft.17.19.

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19

Ito, Toshikazu, and Jun-ichi Abe. "Function of connectives in text-understanding." Japanese journal of psychology 59, no. 4 (1988): 241–47. http://dx.doi.org/10.4992/jjpsy.59.241.

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20

Kuzenko, Н. M. "UNDERSTANDING SEMIOTIC CODES IN TEXT INTERPRETATION." "Scientific notes of V. I. Vernadsky Taurida National University", Series: "Philology. Journalism" 2, no. 1 (2022): 78–83. http://dx.doi.org/10.32838/2710-4656/2022.1-2/13.

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21

Rezeki, Tri Indah, and Rakhmat Wahyudin Sagala. "UNDERSTANDING RECOUNT TEXT THROUGH EGRA IMPLEMENTATION." Jurnal Serunai Bahasa Inggris 13, no. 2 (2022): 54–57. http://dx.doi.org/10.37755/jsbi.v13i2.444.

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Experience, Generalization, Reinforcement, Application (EGRA) technique is suitable for teaching writing. Teaching writing using EGRA techniques executes the students are easier to develop stories based on their experiences. This study focused on investigating the implementation of the EGRA technique in understanding recount text by the students at SMPIT Al-Hijrah 2 Deli Serdang. Specifically, the objective of this study is to find out the effect of the EGRA technique on students' writing ability in recount text. This study employs a quasi-experimental design, including a pre-test and post-tes
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22

Solovyeva, I. V. "TEXT. Understanding: THE problem of defining." Kognitivnye Issledovaniya Yazyka 25 (2016): 81–86. http://dx.doi.org/10.20916/2071-9639-2016-25-81-86.

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23

Uemlianin, Ivan A. "Engaging Text: Assessing paraphrase and understanding." Studies in Higher Education 25, no. 3 (2000): 347–58. http://dx.doi.org/10.1080/713696160.

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24

Mulcahy, Patricia. "Schemata: Cues for Understanding Expository Text." Journal of College Reading and Learning 20, no. 1 (1987): 138–46. http://dx.doi.org/10.1080/10790195.1987.10849910.

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25

Ranum, David L. "Knowledge-based understanding of radiology text." Computer Methods and Programs in Biomedicine 30, no. 2-3 (1989): 209–15. http://dx.doi.org/10.1016/0169-2607(89)90073-4.

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26

M. Katekar, Aparna, and Antara Bhattacharya. "A Survey on Short Text Understanding." International Journal of Engineering Trends and Technology 42, no. 6 (2016): 291–92. http://dx.doi.org/10.14445/22315381/ijett-v42p253.

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27

Miall, David S., and Don Kuiken. "Beyond text theory: Understanding literary response." Discourse Processes 17, no. 3 (1994): 337–52. http://dx.doi.org/10.1080/01638539409544873.

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28

Greco, G., and A. F. Rocha. "The fuzzy logic of text understanding." Fuzzy Sets and Systems 23, no. 3 (1987): 347–60. http://dx.doi.org/10.1016/0165-0114(87)90047-9.

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29

Akimova, Nataliia, та Alina Akimova. "Тext Understanding as a Special Kind of Understanding". PSYCHOLINGUISTICS 24, № 1 (2018): 27–46. http://dx.doi.org/10.31470/2309-1797-2018-24-1-27-46.

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The analysis of modern theories of text understanding are presented in the article. Different theoretical methods and techniques were used for this purpose: deductive and inductive methods, analysis and synthesis, generalization, systematization and modeling as well as some interpretive methods that are based on specific principles of systemic, activity, cognitive and organizational approaches. The author notes that six approaches to the interpretation of understanding can beaccented in modern psychological literature. They are understanding as knowledge, understanding as comprehension, unders
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30

Ivaschenko, Anton, Arkadiy Krivosheev, Anastasia Stolbova, and Oleg Golovnin. "Hybridization of Intelligent Solutions Architecture for Text Understanding and Text Generation." Applied Sciences 11, no. 11 (2021): 5179. http://dx.doi.org/10.3390/app11115179.

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This study proposes a new logical model for intelligent software architecture devoted to improving the efficiency of automated text understanding and text generation in industrial applications. The presented approach introduces a few patterns that provide a possibility to build adaptable and extensible solutions using machine learning technologies. The main idea is formalized by the concept of expounder hybridization. It summarizes an experience of document analysis and generation solutions development and social media analysis based on artificial neural networks’ practical use. The results of
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31

Mohammed Saleh, Awat Ahmad, and Abdulwahid Mushier Mahmoud Dizayee. "Mental processes and understanding of text structure." JOURNAL OF LANGUAGE STUDIES 7, no. 3 (2023): 62–82. http://dx.doi.org/10.25130/lang.7.3.4.

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The title of the research is (Mental processes and understanding of text structure) Mental processes are the events that go on in the brain from the time stimuli enter until the moment decisions are made and reactions to stimuli. We understand linguistic expressions in some way every day without realizing how this process is done. In understanding the text, the reader seeks to understand the intention of the sender, and this process is done in the mind. It depends on the individual's ability and scientific background Every individual is governed by the mind and our thoughts are evaluated by th
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32

Hasanova, Nazakat Aslan. "Cognitive Principles and Mechanisms of Text Understanding." International Journal of Research and Review 9, no. 11 (2022): 432–36. http://dx.doi.org/10.52403/ijrr.20221159.

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The rapid development of text linguistics, which marked the second half of the 20th century, is associated with a whole range of modifications of linguistic values, tasks and program settings. We can talk about the atmosphere of a certain "boom" around this area, which some linguists no longer consider an area, but the foundation, the basis of linguistics as a whole. In the modern interpretation of the text, researchers bring to the fore questions of the communicative plan, the tasks of the conditions for effective communication, which provides an unambiguous interpretation of the units of the
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33

Göthberg, Martin, Cecilia Björck, and Åsa Mäkitalo. "From Drama Text to Stage Text: Transitions of Text Understanding in a Student Theatre Production." Mind, Culture, and Activity 25, no. 3 (2018): 247–62. http://dx.doi.org/10.1080/10749039.2018.1480633.

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34

ESSED, PHILOMENA. "Understanding verbal accounts of racism: Politics and heuristics of reality constructions." Text - Interdisciplinary Journal for the Study of Discourse 8, no. 1-2 (1988): 5–40. http://dx.doi.org/10.1515/text.1.1988.8.1-2.5.

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35

Shobana, J., S. Amutha, and M. Murali. "Understanding Short Text Through Lexical Semantic Analysis." IOP Conference Series: Materials Science and Engineering 1130, no. 1 (2021): 012038. http://dx.doi.org/10.1088/1757-899x/1130/1/012038.

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36

Valikova, Olga A., and Alena S. Demchenko. "Translingual Literary Text: on Problem of Understanding." Polylinguality and Transcultural Practices 17, no. 3 (2020): 352–62. http://dx.doi.org/10.22363/2618-897x-2020-17-3-352-362.

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The given study covers an actual interdisciplinary issue - Russian language, post-Soviet Russian literature in particular, that includes the otherness of multiple ethnic cultures and creates unique images of the world. In the modern conventional sense, culture is replaced by transculture - a space of interaction and mutual repulsion, intertwinement, constellation, overlapping, flowing of cultures into one another. These processes have no and cant have any solidified, final forms that would be determined once and for all. Therefore, the works created in the aesthetics of transculturation are al
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37

Cardoza, Clinton, and Rupali Wagh. "Text analysis framework for understanding cyber-crimes." International Journal of ADVANCED AND APPLIED SCIENCES 4, no. 10 (2017): 58–63. http://dx.doi.org/10.21833/ijaas.2017.010.010.

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38

Cheng, Pengxiang, and Katrin Erk. "Attending to Entities for Better Text Understanding." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 7554–61. http://dx.doi.org/10.1609/aaai.v34i05.6254.

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Recent progress in NLP witnessed the development of large-scale pre-trained language models (GPT, BERT, XLNet, etc.) based on Transformer (Vaswani et al. 2017), and in a range of end tasks, such models have achieved state-of-the-art results, approaching human performance. This clearly demonstrates the power of the stacked self-attention architecture when paired with a sufficient number of layers and a large amount of pre-training data. However, on tasks that require complex and long-distance reasoning where surface-level cues are not enough, there is still a large gap between the pre-trained m
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39

Nasution, Umaruddin. "Wilhelm Dilthey's Hermeneutical Methodology in Understanding Text." Kawanua International Journal of Multicultural Studies 3, no. 1 (2022): 1–4. http://dx.doi.org/10.30984/kijms.v3i1.59.

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The research aims to describe the methodology of hermeneutics Wilhelm Dilthey in understanding text. Dilthey was a philosopher who played an important role in developing hermeneutics as a scientific methodology. The study used library research which guides the hermeneutic books and other documents that give explanations of their thinking. This research also used a historical-philosophical approach and content analysis. The results of this study indicate that Dilthey thought of hermeneutics has three formulations in which the text’s interpretation is experience, expression, and understanding. D
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40

Zuckerman, G. A., and N. A. Kleshch. "Understanding conceptual text sand master in gconcepts." Психологическая наука и образование 22, no. 3 (2017): 19–27. http://dx.doi.org/10.17759/pse.2017220302.

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We address the issue of the relationship between conceptual thinking and understanding of conceptual texts only from the following angle: whether or not can working towards a profound understanding of texts that describe concepts promote the use of these concepts in unusual tasks. Employing the methods of classical statistics and factor analysis, we compare the metasubject outcomes of primary education in two samples of children that differ only in one teaching factor: the experimental classes were consistently working on creating and using conceptual texts. The principle of this teaching work
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41

Tang, Jialong, Hongyu Lin, Meng Liao, et al. "Procedural Text Understanding via Scene-Wise Evolution." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 10 (2022): 11367–75. http://dx.doi.org/10.1609/aaai.v36i10.21388.

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Procedural text understanding requires machines to reason about entity states within the dynamical narratives. Current procedural text understanding approaches are commonly entity-wise, which separately track each entity and independently predict different states of each entity. Such an entity-wise paradigm does not consider the interaction between entities and their states. In this paper, we propose a new scene-wise paradigm for procedural text understanding, which jointly tracks states of all entities in a scene-by-scene manner. Based on this paradigm, we propose Scene Graph Reasoner (SGR),
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42

Xanaliyeva, Ilhama. "Artistic text understanding and its specific characteristics." Terminology Issues, no. 2 (2024): 134. http://dx.doi.org/10.59849/2663-8967.2024.2.134.

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43

Yi, Junkai, Yuan Liu, Zhongbai Jiang, and Zhen Liu. "Text Command Intelligent Understanding for Cybersecurity Testing." Electronics 13, no. 21 (2024): 4330. http://dx.doi.org/10.3390/electronics13214330.

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Research on named entity recognition (NER) and command-line generation for network security evaluation tools is relatively scarce, and no mature models for recognition or generation have been developed thus far. Therefore, in this study, the aim is to build a specialized corpus for network security evaluation tools by combining knowledge graphs and information entropy for automatic entity annotation. Additionally, a novel NER approach based on the KG-BERT-BiLSTM-CRF model is proposed. Compared to the traditional BERT-BiLSTM model, the KG-BERT-BiLSTM-CRF model demonstrates superior performance
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44

Jiang, Junlin Julian, and Xin Li. "Look Ahead Text Understanding and LLM Stitching." Proceedings of the International AAAI Conference on Web and Social Media 18 (May 28, 2024): 751–60. http://dx.doi.org/10.1609/icwsm.v18i1.31349.

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This paper proposes a look ahead text understanding problem with look ahead section identification (LASI) as an example. This problem may appear in generative AI as well as human interactions, where we want to understand the direction of a developing text or conversation. We tackle the problem using transformer-based LLMs. We show that LASI is more challenging than classic section identification (SI). We argue that both bidirectional contextual information (e.g., BERT) and unidirectional predictive ability (e.g., GPT) will benefit the task. We propose two approaches to stitch together BERT and
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45

Lamminpiya, A. M., O. V. Zaschirinskaia, and Yu E. Shelepin. "Psychophysiological analysis of text reading and understanding." Human Physiology 41, no. 2 (2015): 130–34. http://dx.doi.org/10.1134/s0362119715020097.

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46

Sorapure, Madeleine. "Text, Image, Data, Interaction: Understanding Information Visualization." Computers and Composition 54 (December 2019): 102519. http://dx.doi.org/10.1016/j.compcom.2019.102519.

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47

Schmidt, Siegfried J. "Text understanding — A self-organizing cognitive process." Poetics 20, no. 3 (1991): 273–301. http://dx.doi.org/10.1016/0304-422x(91)90010-m.

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48

Zhang, You, Jin Wang, Liang-Chih Yu, Dan Xu, and Xuejie Zhang. "Personalized LoRA for Human-Centered Text Understanding." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 17 (2024): 19588–96. http://dx.doi.org/10.1609/aaai.v38i17.29931.

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Effectively and efficiently adapting a pre-trained language model (PLM) for human-centered text understanding (HCTU) is challenging since user tokens are million-level in most personalized applications and do not have concrete explicit semantics. A standard and parameter-efficient approach (e.g., LoRA) necessitates memorizing numerous suits of adapters for each user. In this work, we introduce a personalized LoRA (PLoRA) with a plug-and-play (PnP) framework for the HCTU task. PLoRA is effective, parameter-efficient, and dynamically deploying in PLMs. Moreover, a personalized dropout and a mutu
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Sorapure, Madeleine. "Text, Image, Data, Interaction: Understanding Information Visualization." Computers and Composition 54 (September 13, 2019): 102519. https://doi.org/10.1016/j.compcom.2019.102519.

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50

Partsey, Ruslan, Vasyl Teslyuk, Oleksandr Maksymets, Vladyslav Humennyy, and Volodymyr Kuzma. "Enhancing 3D scene understanding via text annotations." Eastern-European Journal of Enterprise Technologies 1, no. 2 (133) (2025): 76–84. https://doi.org/10.15587/1729-4061.2025.323757.

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The object of this study is the use of text annotations as a form of 3D scene representation. The paper investigates the task of integrating large-scale language models (LLMs) into complex 3D environments. Using the Embodied Question Answering task as an example, we analyze different types of scene annotations and evaluate the performance of LLMs on a subset of test episodes from the OpenEQA dataset. The aim of the study was to evaluate the effectiveness of textual scene descriptions compared to visual data for solving EQA tasks. The methodology implied estimating the optimal context length fo
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