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Murder On The Vr Express: Studying The Impact Of Thought Experiments At A Distance In Virtual Reality, Andrew Kissel, Krzysztof J. Rechowicz, John B. Shull Jan 2023

Murder On The Vr Express: Studying The Impact Of Thought Experiments At A Distance In Virtual Reality, Andrew Kissel, Krzysztof J. Rechowicz, John B. Shull

Philosophy Faculty Publications

Hypothetical thought experiments allow researchers to gain insights into widespread moral intuitions and provide opportunities for individuals to explore their moral commitments. Previous thought experiment studies in virtual reality (VR) required participants to come to an on-site laboratory, which possibly restricted the study population, introduced an observer effect, and made internal reflection on the participants’ part more difficult. These shortcomings are particularly crucial today, as results from such studies are increasingly impacting the development of artificial intelligence systems, self-driving cars, and other technologies. This paper explores the viability of deploying thought experiments in commercially available in-home VR headsets. We conducted …

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Natural Language Processing In The Legal Domain, Daniel Martin Katz, Dirk Hartung, Lauritz Gerlach, Abhik Jana, Michael J. Ii Bommarito Jan 2023

Natural Language Processing In The Legal Domain, Daniel Martin Katz, Dirk Hartung, Lauritz Gerlach, Abhik Jana, Michael J. Ii Bommarito

Research Collection Yong Pung How School Of Law

In this paper, we summarize the current state of the field of NLP and Law with a specific focus on recent technical and substantive developments. To support our analysis, we construct and analyze a corpus of more than six hundred NLP and Law related papers published over the past decade. Our analysis highlights several major trends. Namely, we document an increasing number of papers written, tasks undertaken, and languages covered over the course of the past decade. We observe an increase in the sophistication of the methods which researchers deployed in this applied context. Slowly but surely, Legal NLP is …

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A Novel Approach To Detecting And Mitigating Keyloggers, Damilola Osedumbi Elelegwu Jan 2023

A Novel Approach To Detecting And Mitigating Keyloggers, Damilola Osedumbi Elelegwu

College of Graduate Studies: Theses & Dissertations

As the digital world gets increasingly ingrained in our daily lives, cyberattacks—especially those involving malware—are growing more complex and common, which calls for developing innovative safeguards. Keylogger spyware, which combines keylogging and spyware functionalities, is one of the most insidious types of cyberattacks. This malicious software stealthily monitors and records user keystrokes, amassing sensitive data, such as passwords and confidential personal information, which can then be exploited. This research work introduces a novel browser extension designed to thwart keylogger spyware attacks effectively. The extension is underpinned by a cutting-edge algorithm that meticulously analyzes input-related processes, promptly identifying and flagging any …

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Spoken Language To Irish Sign Language Machine Translation: A Linguistically Informed Approach, Jesus Aguilar Lopez, Irene Murtagh, Sheila Castilho Jan 2023

Spoken Language To Irish Sign Language Machine Translation: A Linguistically Informed Approach, Jesus Aguilar Lopez, Irene Murtagh, Sheila Castilho

Academic Posters Collection

Many deaf and hard-of-hearing individuals rely on sign language (SL) on a daily basis as a preferred language. Although nowadays there are significant advances on spoken language research, current approaches are often neither linguistically motivated nor tailored to the unique features of SLs. Further research and development are necessary to enhance Sign Language Machine Translation (SLMT) and bring it to a similar level as spoken language MT. This research will endeavour to improve the accuracy and efficiency of SLMT systems, making them more accessible to the Deaf community and empowering deaf and hard of hearing individuals to communicate more effectively …

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Towards Accommodating Gerunds Within The Sign Language Lexicon, Zaid Mohammed, Irene Murtagh Jan 2023

Towards Accommodating Gerunds Within The Sign Language Lexicon, Zaid Mohammed, Irene Murtagh

Academic Posters Collection

This work is part of ongoing research work that focuses on the linguistic analysis and computational description of five different Sign Languages (SLs) namely Irish Sign Language (ISL), Flemish Sign Language (VGT), Dutch Sign Language (NGT), Spanish Sign Language (LSE), and British Sign Language (BSL) as part of the SignON project. This work will be leveraged to inform the development of SL lexicon entries for a Sign Language Machine Translation (SLMT) system. In particular, this research focuses on ISL. We investigate the existence of constructions similar to or equivalent in functionality to gerunds in spoken language, in particular, English. The …

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Neuemot: Mitigating Neutral Label And Reclassifying False Neutrals In The 2022 Fifa World Cup Via Low-Level Emotion, Ademola Adesokan, Sanjay Madria Jan 2023

Neuemot: Mitigating Neutral Label And Reclassifying False Neutrals In The 2022 Fifa World Cup Via Low-Level Emotion, Ademola Adesokan, Sanjay Madria

Computer Science Faculty Research & Creative Works

Sports have been extensively studied for their impact on people's emotional well-being, with research revealing that they have the ability to reduce anxiety and unhappiness while boosting positive emotions1. among all sports, soccer stands out as the most popular and controversial2, eliciting a wide range of emotional reactions from fans, players, officials, and spectators, particularly on social media. While sentiment classifications such as positive, negative, and neutral have been extensively studied, low-level emotions, which refer to more specific and granular emotional states beyond the three basic categories, have yet to be given much attention. This study scraped over 300,000 tweets …

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Robustembed: Robust Sentence Embeddings Using Self-Supervised Contrastive Pre-Training, Javad Asl, Eduardo Blanco, Daniel Takabi Jan 2023

Robustembed: Robust Sentence Embeddings Using Self-Supervised Contrastive Pre-Training, Javad Asl, Eduardo Blanco, Daniel Takabi

School of Cybersecurity Faculty Publications

Pre-trained language models (PLMs) have demonstrated their exceptional performance across a wide range of natural language processing tasks. The utilization of PLM-based sentence embeddings enables the generation of contextual representations that capture rich semantic information. However, despite their success with unseen samples, current PLM-based representations suffer from poor robustness in adversarial scenarios. In this paper, we propose RobustEmbed, a self-supervised sentence embedding framework that enhances both generalization and robustness in various text representation tasks and against diverse adversarial attacks. By generating high-risk adversarial perturbations to promote higher invariance in the embedding space and leveraging the perturbation within a novel contrastive …

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Deeppatent2: A Large-Scale Benchmarking Corpus For Technical Drawing Understanding, Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen Jan 2023

Deeppatent2: A Large-Scale Benchmarking Corpus For Technical Drawing Understanding, Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen

Computer Science Faculty Publications

Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million …

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A Structure-Aware Generative Adversarial Network For Bilingual Lexicon Induction, Bocheng Han, Qian Tao, Lusi Li, Zhihao Xiong Jan 2023

A Structure-Aware Generative Adversarial Network For Bilingual Lexicon Induction, Bocheng Han, Qian Tao, Lusi Li, Zhihao Xiong

Computer Science Faculty Publications

Bilingual lexicon induction (BLI) is the task of inducing word translations with a learned mapping function that aligns monolingual word embedding spaces in two different languages. However, most previous methods treat word embeddings as isolated entities and fail to jointly consider both the intra-space and inter-space topological relations between words. This limitation makes it challenging to align words from embedding spaces with distinct topological structures, especially when the assumption of isomorphism may not hold. To this end, we propose a novel approach called the Structure-Aware Generative Adversarial Network (SA-GAN) model to explicitly capture multiple topological structure information to achieve accurate …

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Claimdistiller: Scientific Claim Extraction With Supervised Contrastive Learning, Xin Wei, Md Reshad Ul Hoque, Jian Wu, Jiang Li Jan 2023

Claimdistiller: Scientific Claim Extraction With Supervised Contrastive Learning, Xin Wei, Md Reshad Ul Hoque, Jian Wu, Jiang Li

Computer Science Faculty Publications

The growth of scientific papers in the past decades calls for effective claim extraction tools to automatically and accurately locate key claims from unstructured text. Such claims will benefit content-wise aggregated exploration of scientific knowledge beyond the metadata level. One challenge of building such a model is how to effectively use limited labeled training data. In this paper, we compared transfer learning and contrastive learning frameworks in terms of performance, time and training data size. We found contrastive learning has better performance at a lower cost of data across all models. Our contrastive-learning-based model ClaimDistiller has the highest performance, boosting …

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The Employees’ Perspective: Situational Leadership Style Flexibility And Effectiveness And Employee Performance In A Technological Organization, Merari Cortes Jan 2023

The Employees’ Perspective: Situational Leadership Style Flexibility And Effectiveness And Employee Performance In A Technological Organization, Merari Cortes

Walden Dissertations and Doctoral Studies

Poor employee performance can have adverse effects on business outcomes. Business leaders are concerned with poor performance, which can minimize profitability and negatively impact business sustainability. Grounded in the Situational Leadership II® model, the purpose of this quantitative correlational study was to examine the relationship between situational leadership style flexibility, effectiveness, and employee performance as perceived by employees, controlling for employee gender, job location, and tenure. A random sample of 99 technology company employees completed the Leader Behavior Analysis II®– Other and the Employee Job Performance measurement tools. Using hierarchical multilinear regression, employee gender, job location, and tenure were entered …

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Mining Health Informatics Job Advertisements: Insights For Higher Education Programs And Job Seekers, Ahmed El Noshokaty, Mohammad A. Al-Ramahi, Omar El-Gayar, Abdullah Wahbeh, Tareq Nasralah Jan 2023

Mining Health Informatics Job Advertisements: Insights For Higher Education Programs And Job Seekers, Ahmed El Noshokaty, Mohammad A. Al-Ramahi, Omar El-Gayar, Abdullah Wahbeh, Tareq Nasralah

Computer Information Systems Faculty Publications (Archived)

This paper used web scraping and data mining to analyze 831 health informatics job advertisements on indeed.com. Results showed that 87% of jobs explicitly required a college degree in a related field, 41% of jobs preferred a graduate degree, while 29% preferred or required professional certification. The analysis showed that preferred skills were analytics problem solving, communication skills, oral communication, interpersonal skills, project management, statistics, and critical thinking. The analysis also showed that college degrees, certifications, and the above-mentioned skill set are in high demand for working in the field of health informatics, especially in states with large populations and …

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Combating Fake News: A Gravity Well Simulation To Model Echo Chamber Formation In Social Media, Jeremy E. Thompson Jan 2023

Combating Fake News: A Gravity Well Simulation To Model Echo Chamber Formation In Social Media, Jeremy E. Thompson

Dartmouth College Ph.D Dissertations

Fake news has become a serious concern as distributing misinformation has become easier and more impactful. A solution is critically required. One solution is to ban fake news, but that approach could create more problems than it solves, and would also be problematic from the beginning, as it must first be identified to be banned. We initially propose a method to automatically recognize suspected fake news, and to provide news consumers with more information as to its veracity. We suggest that fake news is comprised of two components: premises and misleading content. Fake news can be condensed down to a …

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The Shortfalls Of Vulnerability Indexes For Public Health Decision-Making In The Face Of Emergent Crises: The Case Of Covid-19 Vaccine Uptake In Virginia, Lydia Cleveland Sa, Erika Frydenlund Jan 2023

The Shortfalls Of Vulnerability Indexes For Public Health Decision-Making In The Face Of Emergent Crises: The Case Of Covid-19 Vaccine Uptake In Virginia, Lydia Cleveland Sa, Erika Frydenlund

VMASC Publications

Equitable and effective vaccine uptake is a key issue in addressing COVID-19. To achieve this, we must comprehensively characterize the context-specific socio-behavioral and structural determinants of vaccine uptake. However, to quickly focus public health interventions, state agencies and planners often rely on already existing indexes of "vulnerability." Many such "vulnerability indexes" exist and become benchmarks for targeting interventions in wide ranging scenarios, but they vary considerably in the factors and themes that they cover. Some are even uncritical of the use of the word "vulnerable," which should take on different meanings in different contexts. The objective of this study is …

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A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore Jan 2023

A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore

VMASC Publications

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents' perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt …

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Finer Details Of Language Modeling: Text Segmentation, Working Within Resource Limits, And Watermarking, Evan Gordon Lucas Jan 2023

Finer Details Of Language Modeling: Text Segmentation, Working Within Resource Limits, And Watermarking, Evan Gordon Lucas

Dissertations, Master's Theses and Master's Reports

Language modeling is a vast sub-field of natural language processing and this work focuses on solving some specific problems within that field. Technically, the work falls into a number of sub-categories within natural language processing; how to segment texts, improving sparse transformer performance for summarization tasks, character level models for dialect determination, watermarking of large language models, and a general method of incorporating minimal human feedback for continual or online learning. Despite touching on many small areas, they all connect as being related to the very general problem of handling sequential data. Language and text can be thought of as …

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การเรียนรู้เชิงลึกสำหรับเข้ารหัสบัญชีการจำแนกโรคระหว่างประเทศ (ไอซีดี) จากบันทึกเวชระเบียนโดยใช้คลังข้อมูลภาษาไทยและภาษาอังกฤษ, ณัฐชา ซาซุม Jan 2023

การเรียนรู้เชิงลึกสำหรับเข้ารหัสบัญชีการจำแนกโรคระหว่างประเทศ (ไอซีดี) จากบันทึกเวชระเบียนโดยใช้คลังข้อมูลภาษาไทยและภาษาอังกฤษ, ณัฐชา ซาซุม

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้เสนอแบบจำลองสำหรับจำแนกรหัสไอซีดีแบบหลายฉลากเพื่อเป็นตัวช่วยจำแนกรหัสไอซีดี การให้รหัสไอซีดีไม่ครบส่งผลให้โรงพยาบาลไม่ได้รับเงินค่าชดเชยอย่างเหมาะสม เราจึงมุ่งเน้นที่จะช่วยโรงพยาบาลให้รหัสไอซีดีอย่างครบถ้วนในขั้นตอนการเบิกจ่ายเงินค่ารักษาพยาบาลซึ่งผลลัพธ์ที่ได้คือการสนับสนุนทางการเงินแก่โรงพยาบาล โดยปกติแล้วปัญหาการให้รหัสไอซีดีแบบหลายฉลากเป็นชุดข้อมูลบันทึกเวชระเบียนที่มีการกระจายตัวแบบหางยาวซึ่งไม่ควรละทิ้งข้อมูลใด ๆ ดังนั้น การจำแนกแบบหลายฉลากของเราจึงเป็นการรวมกันของวิธีการรวมแบบจำลองการเรียนรู้เชิงลึกทั้งสาม (Bidirectional Long-short term memory, Convolutional neural network and Transformer encoder) ด้วยการเลือกค่าทำนายสูงสุดและแบบจำลองทางสถิติคือ Multinomial Naïve Bayes ร่วมกับวิธี Binary Relevance ในส่วนของแบบจำลองการเรียนรู้เชิงลึกจะรับผิดชอบกลุ่มรหัสไอซีดีทั่วไป (โรคที่พบบ่อย) ในขณะที่แบบจำลองทางสถิติจะจัดการกับกลุ่มรหัสไอซีดีพบยาก (โรคที่ผู้ป่วยไม่ค่อยเป็น) ผลการทำนายรหัสไอซีดี-10 จากบันทึกการรักษาด้วยแบบจำลองนี้ให้ค่า Jaccard index ที่ 0.792 สำหรับกลุ่มรหัสไอซีดีทั่วไปและที่ 0.205 สำหรับกลุ่มรหัสไอซีดีพบยาก ส่วนของผลการทำนายรหัสไอซีดี-9 จากบันทึกการให้ยา (หัตถการรักษา) ให้ค่า Jaccard index ที่ 0.963 สำหรับกลุ่มรหัสไอซีดีทั่วไปและที่ 0.201 สำหรับกลุ่มรหัสไอซีดีพบยาก ซึ่งแบบจำลองนี้มีความสามารถในการแนะนำรหัสไอซีดีที่ขั้นตอนการเบิกจ่ายเงินค่ารักษาพยาบาล

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การเปรียบเทียบขั้นตอนวิธีการเรียนรู้ของเครื่องและโครงข่ายประสาทเทียมสำหรับการตรวจคะแนนเรียงความภาษาไทยอัตโนมัติ, สุทธิชาย สุริยสัตย์ Jan 2023

การเปรียบเทียบขั้นตอนวิธีการเรียนรู้ของเครื่องและโครงข่ายประสาทเทียมสำหรับการตรวจคะแนนเรียงความภาษาไทยอัตโนมัติ, สุทธิชาย สุริยสัตย์

Chulalongkorn University Theses and Dissertations (Chula ETD)

ตัวแทนนักเรียนไทยได้คะแนนการประเมินด้านการอ่านค่อนข้างตํ่า ในการสอบประเมินสมรรถนะนักเรียนมาตรฐานสากล (Programme for International Student Assessment PISA) หลายงานวิจัยพบว่าทักษะด้านการอ่านสามารถถูกพัฒนาผ่านการเขียนเช่น การเขียนเรียงความได้ แต่การตรวจเรียงความนั้นใช้เวลาค่อนข้างนาน ระบบการตรวจคะแนนเรียงความโดยอัตโนมัติได้ถูกพัฒนาขึ้นเพื่อช่วยเหลือผู้ตรวจเรียงความ อีกทั้งยังสามารถแสดงผลการทำนายคะแนนให้กับผู้เขียนเรียงความได้ทันทีด้วย เนื่องจากงานวิจัยด้านการตรวจคะแนนเรียงความภาษาไทยโดยอัตโนมัติมีน้อยมาก งานวิจัยนี้จึงมุ่งเน้นไปที่การเปรียบเทียบแบบจำลองการให้คะแนนภาษาไทยโดยอัตโนมัติ ที่ใช้แบบจำลองการเรียนรู้ของเครื่องและการเรียนรู้เชิงลึก ที่ได้ถูกรายงานว่ามีประสิทธิภาพที่ดีในการทำนายคะแนนเรียงในความภาษาอังกฤษ งานวิจัยนี้พบว่าแบบจำลอง XGBoost มีประสิทธิภาพดีที่สุดในหลายสถานการณ์ที่ถูกพิจารณา และ แบบจำลองหน่วยความจำระยะสั้นแบบยาวที่ใช้ฟีเจอร์ที่สกัดจากข้อความโดยอัตโนมัติ มีประสิทธิภาพดีที่สุดในกลุ่มแบบจำลองการเรียนรู้เชิงลึก

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Groundwater Potential Mapping At Highly Populated Sub-Districts Of Thimphu District Using Fuzzy Analytic Hierarchy Process, Thongley Thongley, Tshering Choki, Kuenzang Choden Jan 2023

Groundwater Potential Mapping At Highly Populated Sub-Districts Of Thimphu District Using Fuzzy Analytic Hierarchy Process, Thongley Thongley, Tshering Choki, Kuenzang Choden

Applied Environmental Research

Groundwater is important when there is an insufficient spring water supply for daily needs. The population growth and expansion of the cities demand more water. Thimphu is the capital city of Bhutan and facing water shortage in recent times due to urban expansion and population growth. This study aims to find the potential area for groundwater using the Fuzzy Analytic Hierarchy Process. The factors used for this study are elevation, slope, curvature, topographic wetness index, drainage density, normalized difference vegetation index, distance from fault density, rainfall distribution map, soil texture map, and drainage density. The rating for the factors and …

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Simplified Music Playlist Recommendation Using Sequential-Based Gated Recurrent Unit For Policy And Action Determination, Chanapa Channarong Jan 2023

Simplified Music Playlist Recommendation Using Sequential-Based Gated Recurrent Unit For Policy And Action Determination, Chanapa Channarong

Chulalongkorn University Theses and Dissertations (Chula ETD)

Recommendation systems are crucial for helping users discover music tailored to their preferences on streaming services. Reinforcement learning is a popular method for music recommendations. However, previous approaches have struggled with overfitting. The agent may become problematic for the new user context if, after a learning phase, it starts to predict actions only based on previous interactions. To overcome this limitation, previous methods require retraining, which require resetting all parameters in the agent. This study introduces the Policy GRU-RL method, which combines sequential-based learning and reinforcement learning to address overfitting without resetting all parameters. It utilizes a recurrent network by …

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Solving Cold Start Problems Of Recommender Systems Using Generative Models, Panjawat Rungtranont Jan 2023

Solving Cold Start Problems Of Recommender Systems Using Generative Models, Panjawat Rungtranont

Chulalongkorn University Theses and Dissertations (Chula ETD)

Recommender systems are essential for enhancing user experiences on digital platforms, but they often struggle with suggesting new items lacking interaction data, known as the cold-start item problem. This study introduces "LLM-search," a novel method combining advanced language models (PaLM-2) with data augmentation techniques to address this challenge. LLM-search analyzes users' interactions to identify new items related to their preferences. It then employs a search engine to find cold items based on these preferences, effectively creating synthetic cold items interaction for training the recommender model. An experiment using the 2018 Amazon review dataset across sports & outdoors, groceries, and electronics …

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Article Feed Recommendation For Thai Social Network Application Using Article Context Based On Deep Learning, Pannawit Athipatcharawat Jan 2023

Article Feed Recommendation For Thai Social Network Application Using Article Context Based On Deep Learning, Pannawit Athipatcharawat

Chulalongkorn University Theses and Dissertations (Chula ETD)

In recent years, social media applications have exhibited significant growth in the number of users. Enhancing content alignment with user preferences is essential in developing a sophisticated recommendation system. Neural networks have become pivotal in improving the performance of recommendation systems. However, the utilization of auxiliary information and text data remains markedly underexplored, especially in the context of Thai recommendation systems. Therefore, this study aims to bridge this gap by developing a recommendation system tailored to Thai social media applications. We focus on leveraging supplementary information and analyzing text features to gain deeper insights into user preferences while addressing the …

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Disciplines Different Of Fine-Grained Acknowledged Entity：A Case Of Doctoral Dissertations In Chinese Humanities And Social Sciences, Jiaxin He, Shijin Zhang, Jiayu Zheng, Xinlong Chu, Chengzhi Zhang Jan 2023

Disciplines Different Of Fine-Grained Acknowledged Entity：A Case Of Doctoral Dissertations In Chinese Humanities And Social Sciences, Jiaxin He, Shijin Zhang, Jiayu Zheng, Xinlong Chu, Chengzhi Zhang

Journal of Scientific Information Research

[Purpose/significance]Thesis acknowledgment is a public text in which the authors express their gratitude to individuals and institutions those support their research. It is helpful to understand the individuals and institutions that play a role in the cultivation of doctoral candidate in different disciplines by extracting the entities of acknowledgment and comparing the distribution of the objects of acknowledgment in the dissertations of different disciplines.[Method/process]In this paper, we gained more than 60 000 Chinese doctoral dissertations acknowledgment of 21 humanities and social sciences disciplines, extracted acknowledged entities from acknowledgment, and constructed a fine-grained classification system of acknowledgment entities. The classification system …

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Explainable Machine Learning For Evapotranspiration Prediction, Bamory Koné, Rima Grati, Bassem Bouaziz, Khouloud Boukadi Jan 2023

Explainable Machine Learning For Evapotranspiration Prediction, Bamory Koné, Rima Grati, Bassem Bouaziz, Khouloud Boukadi

All Works

No abstract provided.

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More Human Than Human: Llm-Generated Narratives Outperform Human-Llm Interleaved Narratives, Zoie Zhao, Sophie Song, Bridget Duah, Jamie C. Macbeth, Scott Carter, Monica Van, Nayeli Bravo, Matthew Klenk, Katherine Sieck, Alexandre Filipowicz Jan 2023

More Human Than Human: Llm-Generated Narratives Outperform Human-Llm Interleaved Narratives, Zoie Zhao, Sophie Song, Bridget Duah, Jamie C. Macbeth, Scott Carter, Monica Van, Nayeli Bravo, Matthew Klenk, Katherine Sieck, Alexandre Filipowicz

Computer Science: Faculty Publications

Narrative story generation has gained emerging interest in the field of large language models. The present paper aims to compare stories generated by an LLM only (non-interleaved) with those generated by interleaving human-generated and LLM-generated text (interleaved). The study’s hypothesis is that interleaved stories would perform better than non-interleaved stories. To verify this hypothesis, we conducted two tests with roughly 500 participants each. Participants were asked to rate stories of each type, including an overall score or preference and four facets—logical soundness, plausibility, understandability, and novelty. Our findings indicate that interleaved stories were in fact less preferred than non-interleaved stories. …

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Image Schema Decompositions Of The Conceptual Dependency Ingest Primitive: A Study Of Paraphrases, Jamie C. Macbeth, Alexis Kilayko, Zoie Zhao, Sophie Song, Winniw X. Zheng Jan 2023

Image Schema Decompositions Of The Conceptual Dependency Ingest Primitive: A Study Of Paraphrases, Jamie C. Macbeth, Alexis Kilayko, Zoie Zhao, Sophie Song, Winniw X. Zheng

Computer Science: Faculty Publications

One of the hallmarks of the Schank-Minsky Conceptual Dependency Trans-Frames meaning representation system is that it attempts to express complex meanings by building large and complex conceptual structures using a relatively small number of primitives. Recently comparisons of image schemas with Conceptual Dependency primitives revealed ways of possibly reducing the number of primitives while maintaining the expressiveness of the set—an important research goal because it increases the flexibility and richness of the primitive-decomposed structures in a way that better approximates human cognition. Inspired by this prior work, we employ a paraphrase generation system to explore the replacement of the Conceptual …

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Exploring The Evolution Of Ai Integration In English As A Foreign Language Education: A Scopus-Based Bibliometric Analysis (1997-2023), Mohanad G. Yaseen, Sara S. Alnakeeb Jan 2023

Exploring The Evolution Of Ai Integration In English As A Foreign Language Education: A Scopus-Based Bibliometric Analysis (1997-2023), Mohanad G. Yaseen, Sara S. Alnakeeb

Mesopotamian Journal of Computer Science

Significant scholarly interest has been focused on the use of AI in English as a Foreign Language (EFL) instruction because it presents novel opportunities for improving language learning contexts and pedagogical approaches. This study provides an in-depth investigation into how AI is revolutionizing English as a foreign language (EFL) instruction, with special focus on the ways in which this technology can help students acquire a language in a fun, engaging, and one-on-one setting. This research examines the ethical and sociological implications of the broad integration of AI technology into language learning environments, highlighting major trends and identifying critical gaps through …

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Nidus Idearum. Scilogs, Xi: In-Turns And Out-Turns, Florentin Smarandache Jan 2023

Nidus Idearum. Scilogs, Xi: In-Turns And Out-Turns, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this eleventh book of scilogs – called in-turns and out-turns –, one may find new and old questions and solutions, referring mostly to topics on Neutrosophy, but also Multispace, with miscellaneous addition of topics on Physics, Mathematics, or Sociology – email messages to research colleagues, or replies, notes about authors, articles, or books, spontaneous ideas, and so on.

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New Similarity And Entropy Measures Of Temporal Complex Neutrosophic Set And Its Application In Multi-Criteria Decision Making, Luong Thi Hong Lan, Nguyen Tho Thong, Nguyen Long Giang, Florentin Smarandache, Vo Si Nam, Dinh Van Dzung Jan 2023

New Similarity And Entropy Measures Of Temporal Complex Neutrosophic Set And Its Application In Multi-Criteria Decision Making, Luong Thi Hong Lan, Nguyen Tho Thong, Nguyen Long Giang, Florentin Smarandache, Vo Si Nam, Dinh Van Dzung

Branch Mathematics and Statistics Faculty and Staff Publications

The Temporal complex neutrosophic set (TCNS) is an effective structure for resolving information that has uncertain, indeterminate, and timerelated factors in decision-making problems. In the last decade, many researchers focused on estimating the vagueness and ambiguity in knowledge using the theory of neutrosophic sets or extensions of neutrosophic sets. Similarity and entropy measures are valuable tools to measure information with the aim of dealing with real-life multi-criteria decisionmaking (MCDM) problems. However, the existing method did not care or interest in the information measures of TCNS. This paper proposes several new similarity and entropy measures under the TCNS environment. The suggested …

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The Encyclopedia Of Neutrosophic Researchers, Vol. 6, Florentin Smarandache, Maikel Yelandi Leyva Vázquez, Jesús Estupiñán Ricardo Jan 2023

The Encyclopedia Of Neutrosophic Researchers, Vol. 6, Florentin Smarandache, Maikel Yelandi Leyva Vázquez, Jesús Estupiñán Ricardo

Branch Mathematics and Statistics Faculty and Staff Publications

Este es el Sexto volumen de la Enciclopedia de Investigadores Neutróficos, editados a partir de materiales ofrecidos por los autores que respondieron a la invitación del editor. Los autores se enumeran alfabéticamente. La introducción contiene una breve historia de la neutrosófica, y en especial se sus impacto en latinoamérica junto con enlaces a los principales artículos y libros. Conjunto neutrosófico, lógica neutrosófica, probabilidad neutrosófica, estadística neutrosófica, medida neutrosófica, precálculo neutrosófico, cálculo neutrosófico, psicología neutrosófica, sociología neutrosófica etc., están ganando una atención significativa en resolver muchos problemas de la vida real que implican incertidumbre, imprecisión, vaguedad, incompletitud, inconsistencia e indeterminación. En …

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