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Enhancing Reinforcement Learning Finetuned Text-to-Image Generative Model Using Reward Ensemble 20th

Enhancing Reinforcement Learning Finetuned Text-to-Image Gen...

引用

20th International Conference on Intelligent Tutoring Systems (ITS)

作者： Back, Kyungryul Piao, XinYu Kim, Jong-Kook Korea Univ Sch Elect Engn Seoul South Korea

ISBN: (纸本)9783031630309;9783031630316

In recent years, advanced diffusion models have shown good performance in converting text prompts into high-quality images. However, aligning the generated images to human preferences remains challenging due to the biases in training. Previous researches have attempted to address this problem by incorporating reinforcement learning and human feedback into the denoising diffusion models. However, such approaches often encounter over-optimization, commonly referred to as the reward hacking problem. This paper introduces a simple and effective ensemble approach that combines multiple reward models to optimize the overall reward structure. This proposed method successfully overcomes the over-optimization problem in the diffusion model's finetuning process. Both quantitative and qualitative results demonstrate the effectiveness of the proposed approach to generate an image that is a more realistic representation.

关键词： Generative Model Text-to-Image Reinforcement Learning

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Construction and Practice of Financial Management Professional Curriculum System Based on OBE Philosophy 13th

Construction and Practice of Financial Management Profession...

引用

13th International Conference on Design, User Experience and Usability (DUXU)

作者： Fang, Fang Chen, XiaoShi Li, Qing Lan Guangzhou City Univ Technol Guangzhou 510800 Peoples R China

ISBN: (纸本)9783031613616;9783031613623

This paper examines the construction strategy, implementation path and construction practice of the curriculum system in the reform of financial management professional talent training under the concept of OBE. Through literature review, case study, questionnaire survey method and other methods, this paper in-depth study of the application of the OBE concept in financial management education and puts forward a combination of social demand, student development and educational objectives of the curriculum reverse design construction framework system, including the development of student training from the talent training objectives of the expected results, to determine the course teaching content, teaching methods, sound and diversified assessment and evaluation system, continuous improvement of the whole process. Improvement of the whole process. The empirical analysis part will verify the implementation effect of the curriculum system through the data analysis of the practice process and the results of the questionnaire survey;summarize the results of the practice and discuss the direction of the future research and the problems that may be encountered. The findings of this paper are of great theoretical and practical significance for optimizing the curriculum design of financial management majors and improving students' professionalism and comprehensive ability.

关键词： OBE (outcome-based) financial management curriculum system

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LLM-Based Course Comprehension Evaluator 20th

LLM-Based Course Comprehension Evaluator

引用

20th International Conference on Intelligent Tutoring Systems (ITS)

作者： Zografos, George Kefalidis, Vasileios Moussiades, Lefteris Democritus Univ Thrace Kavala 65404 Greece

ISBN: (纸本)9783031630279;9783031630286

Large language models (LLMs) like GPT-4 reshape intelligent tutoring systems by enabling nuanced natural language interactions. Leveraging LLMs' capabilities, this study introduces an innovative Lesson Comprehension Evaluator, utilizing advanced Natural Language Processing (NLP) methods and Augmented Retrieval Generation (RAG) to assess course material comprehension. Through a web interface, students engage with tailored questions and receive feedback, fostering immersive learning experiences. Each response undergoes rigorous evaluation against a ground truth LLM-generated knowledge base, encompassing semantic comprehension, specificity, and correctness metrics. These evaluations provide insights into students' course understanding, informing future pedagogical strategies. By incorporating auditory options for accessibility and gamification elements for enhanced engagement, this approach facilitates self-paced, deeper learning, fostering dynamic and enriching learning environments.

关键词： Intelligent Tutoring Systems GPT-4 Retrieval Augmented Generation (RAG)

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Generator of Personalised Training Games Activities: A Conceptual Design Approach 12th

Generator of Personalised Training Games Activities: A Conce...

引用

12th International Conference on Games and Learning Alliance (GALA)

作者： Lemoine, Berenice Laforcade, Pierre Le Mans Univ LIUM Comp Sci Lab Laval France

ISBN: (纸本)9783031490644;9783031490651

Memorizing declarative knowledge requires repetition, which can become wearing for learners. In addition, redundant game activities, offering unbalanced challenges in relation to the player's skills, can also lead to a sense of boredom. To reduce this feeling, learning games must provide adapted and varied activities. Automated generation is one way of building such activities. This article proposes a conceptual framework for the design of activity generators for training declarative knowledge in Roguelite games. The framework has been applied in the context of the AdapTABLES project aiming at multiplication tables training.

关键词： Modelling Training Generation Design Serious Games

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Exploring the Methodological Contexts and Constraints of Research in Artificial Intelligence in Education 20th

Exploring the Methodological Contexts and Constraints of Res...

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20th International Conference on Intelligent Tutoring Systems (ITS)

作者： Chounta, Irene-Angelica Limbu, Bibeg van der Heyden, Lisa Univ Duisburg Essen Dept Human Ctr Comp & Cognit Sci Duisburg Germany

ISBN: (纸本)9783031630279;9783031630286

In this paper, we present a Systematic Literature Review (SLR) on the state-of-the-art in Artificial Intelligence in Education (AIED) focusing on methodological contexts and constraints of the research landscape. To do so, we built on existing works and extended them to cover the latest research advancements in the field over the past five years. We aimed at covering all educational levels and retrieving important data regarding the planning and execution of research studies and the robustness of results. In total, we reviewed 181 papers and answered three research questions, relating to the educational context of AI use, the methodology and study design utilized in AIED research, and the type of AI algorithms and technologies used in education. Our findings suggest that research in AIED primarily focuses on formal, higher education and that there is a demand for robust and rigorous scientific evidence of the effectiveness and impact of AIED. Furthermore, the findings indicate that the most popular AI technologies currently studied are traditional AI algorithms, usually used for prediction, classification, or clustering. Based on our analysis, we discuss practical implications that can serve as inspiration and guidance for future research initiatives.

关键词： artificial intelligence in education research methodology systematic literature review

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Are Game Elements Fueling Learners' Motivation via Positive Affect? 12th

Are Game Elements Fueling Learners' Motivation via Positive ...

引用

12th International Conference on Games and Learning Alliance (GALA)

作者： Huber, Stefan E. Lindstedt, Antero Kiili, Kristian Ninaus, Manuel Karl Franzens Univ Graz Dept Psychol Graz Austria Tampere Univ Fac Educ & Culture Tampere Finland Univ Tubingen LEAD Grad Sch & Res Network Tubingen Germany

ISBN: (纸本)9783031490644;9783031490651

The use of game elements in learning tasks is often motivated by the aim of utilizing their motivational capabilities. Even if game elements do not directly affect cognitive learning outcomes, they can keep learners engaged and support long-term loyalties. In this contribution, we present an investigation of the effect of game elements with a specific focus on affective and motivational aspects. In particular, we report a value-added online experiment, comparing a game-based version with a non-game-based version of an association learning task. In total, 61 participants completed the experiment. While we find comparable cognitive learning outcomes, we find medium and large differences in affective and motivational outcomes. Game elements are associated with an increase in positive affect and increased perceived competence compared to the non-game-based task. The game-based task was further perceived significantly more attractive and stimulating. Mediation models revealed that the increased cognitive cost introduced by game elements was effectively balanced by their benefits regarding motivation. The latter was partially mediated by changes in positive affect. In sum, the net cognitive outcome was the same for both tasks, but learners in the game-based condition were more positively affected, more motivated and felt more competent. Implications and future research directions are discussed.

关键词： game elements association learning cognition motivation affect

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Player-Replaceability and Forensic Support Are Two Sides of the Same (Crypto) Coin 27th

Player-Replaceability and Forensic Support Are Two Sides of ...

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27th International Conference on Financial Cryptography and Data Security (FC)

作者： Sheng, Peiyao Wang, Gerui Nayak, Kartik Kannan, Sreeram Viswanath, Pramod Univ Illinois Champaign IL 61820 USA Beijing Acad Blockchain & Edge Comp Beijing Peoples R China Duke Univ Durham NC 27708 USA Univ Washington Seattle WA 98195 USA Princeton Univ Princeton NJ 08544 USA

ISBN: (纸本)9783031477539;9783031477546

Player-replaceability is a property of a blockchain protocol that ensures every step of the protocol is executed by an unpredictably random (small) set of players;this guarantees security against a fully adaptive adversary and is a crucial property in building permissionless blockchains. Forensic Support is a property of a blockchain protocol that provides the ability, with cryptographic integrity, to identify malicious parties when there is a safety violation;this provides the ability to enforce punishments for adversarial behavior and is a crucial component of incentive mechanism designs for blockchains. Player-replaceability and strong forensic support are both desirable properties, yet, none of the existing blockchain protocols have both properties. Our main result is to construct a new BFT protocol that is player-replaceable and has maximum forensic support. The key invention is the notion of a "transition certificate", without which we show that natural adaptations of extant BFT and longest chain protocols do not lead to the desired goal of simultaneous player-replaceability and forensic support. (The full version of paper is available in https://***/2022/1513.)

关键词： Blockchain

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Analyzing and Predicting Meetup Mobs Outcome Via Statistical Analysis and Deep Learning 17th

Analyzing and Predicting Meetup Mobs Outcome Via Statistical...

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17th International Conference on Social, Cultural, and Behavioral Modeling (SBP-BRiMS)

作者： Al-khateeb, Samer Burright, Jack Fernandes, Steven L. Agarwal, Nitin Creighton Univ Omaha NE 68178 USA UA Little Rock COSMOS Res Ctr Little Rock AR 72204 USA

ISBN: (纸本)9783031722400;9783031722417

We refer to a "mob" as an event that is organized via social media, email, SMS, or other forms of digital communication technologies in which a group of people (who might have an agenda) get together online or offline to collectively conduct an act and then disperse (quickly or over a long period). To an outsider, such an event may seem arbitrary. However, a sophisticated amount of coordination is involved. *** is an "Event-Based Social Network" (EBSN) focused on bringing like-minded people together. Meetup hosts a wide range of events, making it crucial and well-suited for studying various events in general and mobs in particular. In this research, we collected data from Meetup and employed statistical analysis to help us better understand the data. Additionally, we utilized a deep neural network-based method to create two classifiers capable of predicting the Meetup mob outcome (success or failure) with great accuracy.

关键词： Mobs Modeling Deep Learning Meetup Statistical Analysis Event-Based Social Network

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Towards Multilingual LLM-Based Approaches for Automatic Dewey Decimal Classification 28th

Towards Multilingual LLM-Based Approaches for Automatic Dewe...

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28th International Conference on Linking Theory and Practice of Digital Libraries (TPDL)

作者： Ho, Clara Wan Ching Weber, Tobias Fritze, Thorsten Risse, Thomas Goethe Univ Frankfurt Univ Lib Frankfurt Germany

ISBN: (纸本)9783031724398;9783031724404

The usage of classification systems is a standard method in libraries to organize all kind of materials. The Dewey Decimal Classification System (DDC) is widely used for this task. Even though approaches exist since the 1970s to automate this classification task, it is most often still a time consuming manual process. With the constantly increasing number of publications the need for automation support is growing. Current approaches have certain limitations e.g. only mono- or bi-lingual support, limited accuracy for research domains, limited to higher levels in the DDC hierarchies. The usage of Large Language Models (LLMs) opens new possibilities to support librarians in their work. In this paper we present preliminarily a study to evaluate the usage of BERT to handle a DDC classification task in the linguistic domain. In addition, we analyze the effect of a more condensed representation of full text on the performance of LLMs for this task. Results on multilingual texts are comparable to recent performances on monolingual inputs.

关键词： Classification linguistics DDC Large Language Models

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OpenPSS: An Open Page Stream Segmentation Benchmark 28th

OpenPSS: An Open Page Stream Segmentation Benchmark

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28th International Conference on Linking Theory and Practice of Digital Libraries (TPDL)

作者： van Heusden, Ruben Kamps, Jaap Marx, Maarten Univ Amsterdam Informat Retrieval Lab Amsterdam Netherlands Univ Amsterdam Fac Humanities Amsterdam Netherlands

ISBN: (纸本)9783031724367;9783031724374

In recent years, an increasing number of companies and institutions have begun the process of digitizing their physical records to promote digital access and searchability of their collections. For cost-efficiency, documents are often scanned in consecutively, resulting in large PDF files consisting of many documents. Although cost-effective, this practice can be harmful for searchability when these concatenated documents are used to build a search engine. The task of Page Stream Segmentation is concerned with recovering the original document boundaries through the analysis of the text and/or images of these PDF files. Currently, many of the approaches to solving this problem make use of machine learning techniques that require significant amounts of training data. However, due to the sometimes sensitive nature of the data, few large datasets exist, and there is a lack of agreed-upon metrics to measure system performance. In an effort to resolve these issues and provide a comprehensive overview of the state of the field, we constructed the OpenPSS benchmark, consisting of two large public datasets and a comprehensive study of various types of approaches, evaluated using multiple evaluation metrics. The datasets originated from several Dutch government institutions, cover a heterogeneous set of topics, and total roughly 141 thousand pages from around 32 thousand documents. The experimental results show that ensemble methods using both the text and image representations of pages are superior to uni-modal methods, and that image-based neural methods are not as robust as text models when evaluated on out-of-distribution data.

关键词： Page Stream Segmentation benchmark text classification

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