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Evaluation of the Effectiveness of Prompts and Generative AI Responses 37th

Evaluation of the Effectiveness of Prompts and Generative AI...

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37th International Conference on computer Applications in Industry and Engineering

作者： Bandi, Ajay Zeng, Ruida Northwest Missouri State Univ Sch Comp Sci & Informat Syst 800 Univ Dr Maryville MO 64468 USA Brown Univ Dept Comp Sci Providence RI 02912 USA

ISBN: (纸本)9783031762727;9783031762734

Our paper proposes a comprehensive framework to evaluate the effectiveness of prompts and the corresponding responses generated by Generative Artificial Intelligence (GenAI) systems. To do so, our evaluation framework incorporates both objective metrics (accuracy, speed, relevancy, and format) and subjective metrics (coherence, tone, clarity, verbosity, and user satisfaction). A sample evaluation is performed on prompts send to Gemini and ChatGPT GenAI models. Additionally, our evaluation framework employs various feedback mechanisms, such as surveys, expert interviews, and automated reinforcement learning from human feedback (RLHF), to iteratively enhance the performance and reliability of GenAI models. By providing a holistic approach to evaluating and improving prompt-response effectiveness, our evaluation framework contributes to the development of more credible and user-friendly AI systems.

关键词： Generative AI (GenAI) Prompt Engineering Evaluation Framework Reinforcement Learning from Human Feedback (RLHF)

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Incentives for Early Arrival in Cooperative Games: A Summary 1st

Incentives for Early Arrival in Cooperative Games: A Summary

引用

1st International Workshop on Mechanism Design in Social Networks

作者： Ge, Yaoxin Zhang, Yao Zhao, Dengji ShanghaiTech Univ Shanghai Peoples R China

ISBN: (纸本)9789819602131;9789819602148

The present study concerns itself with the analysis of cooperative games in which players are required to join the game in a sequential manner. In such games, the value generated by those players who have joined at any given point must be irrevocably divided among the other players. Two criteria are proposed for the value division mechanism: firstly, that players should have incentives to join as early as possible, and secondly, that the division should be considered fair. In order to satisfy this requirement, it is necessary that each player's expected share in the mechanism should be equal to her Shapley value, assuming that the players' arrival order is uniformly random. The primary technical contribution of this study is a comprehensive characterisation of 0-1 value games for which suitable mechanisms are available. We demonstrate that the Rewarding First Critical Player (RFC) mechanism is complete, in that a 0-1 value function admits a mechanism with the aforementioned properties if and only if RFC satisfies them. Furthermore, we provide an analytical characterisation of all such value functions.

关键词： Cooperative Games Early Arrival Online Mechanisms

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High-Precision Method to Reduce Overfitting in ANNs Using Highly Uniform Chaotic Sequences 8th

High-Precision Method to Reduce Overfitting in ANNs Using Hi...

引用

2024 World Congress in computer science, computer Engineering and Applied Computing-CSCE

作者： Shirzadeh, Samad Ferens, Ken Kinsner, Witold Univ Manitoba Winnipeg MB R3T 2N2 Canada

ISBN: (纸本)9783031856273;9783031856280

Overfitting is a common problem in various artificial neural networks (ANNs) because of limited data, a complex model, or a lack of regularization. Chaos injection is one of the effective solutions to prevent overfitting for multi-layer perceptron neural networks (MLPs). This paper presents an improved chaotic injection technique utilizing the enhanced multiparametric tent map (MTM). Using this heuristic technique, we choose a set of control parameters with the most uniformity according to the Kolmogorov-Smirnov (KS) method. When the MTM is used in training an ANN, the uniformity of each generated sequence is greatly reduced due to the random selection of the initial value of a sequence. To solve this problem, we generated all the sequences before training time using the MTM based on dataset size, number of neurons in each layer, batch size, and number of k-folds. Next, we normalized the sequences through a novel chaotic-sequence normalization and probability mass function (PMF) equalization procedure to ensure they were uniform, and finally, we stored them in a table. During training, the uniform sequences were read from the table and were injected into the learning fabric of the ANN. The experimental results demonstrated a superior accuracy of our proposed scheme in comparison with the latest techniques according to the following performance metrics: accuracy (ACC), F1-score (F1), negative-predictive value (NPV), positive-predictive value (PPV), sensitivity (SN), and specificity (SP).

关键词： Overfitting Generalization Error Chaotic Injection Artificial Neural Networks

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NeuroLGP-SM: A Surrogate-Assisted Neuroevolution Approach Using Linear Genetic Programming 7th

NeuroLGP-SM: A Surrogate-Assisted Neuroevolution Approach Us...

引用

7th International Conference on Optimization and Learning

作者： Stapleton, Fergal Cody-Kenny, Brendan Galvan, Edgar Maynooth Univ Hamilton Inst CS Dept Naturally Inspired Comp Res Grp Maynooth Kildare Ireland Sema Baltimore MD USA

ISBN: (纸本)9783031779404;9783031779411

Evolutionary algorithms are increasingly recognised as a viable computational approach for the automated optimisation of deep neural networks (DNNs) within artificial intelligence. This method extends to the training of DNNs, an approach known as neuroevolution. However, neuroevolution is an inherently resource-intensive process, with certain studies reporting the consumption of thousands of GPU days for refining and training a single DNN network. To address the computational challenges associated with neuroevolution while still attaining good DNN accuracy, surrogate models emerge as a pragmatic solution. Despite their potential, the integration of surrogate models into neuroevolution is still in its early stages, hindered by factors such as the effective use of high-dimensional data and the representation employed in neuroevolution. In this context, we address these challenges by employing a suitable representation based on Linear Genetic Programming, denoted as NeuroLGP, and leveraging Kriging Partial Least Squares. The amalgamation of these two techniques culminates in our proposed methodology known as the NeuroLGP-Surrogate Model (NeuroLGP-SM). For comparison purposes, we also code and use a baseline approach incorporating a repair mechanism, a common practice in neuroevolution. Notably, the baseline approach surpasses the renowned VGG-16 model in accuracy. Given the computational intensity inherent in DNN operations, a singular run is typically the norm. To evaluate the efficacy of our proposed approach, we conducted 96 independent runs spanning a duration of 4weeks. Significantly, our methodologies consistently outperform the baseline, with the SM model demonstrating superior accuracy or comparable results to the NeuroLGP approach. Noteworthy is the additional advantage that the SM approach exhibits a 25% reduction in computational requirements, further emphasising its efficiency for neuroevolution.

关键词： Neuroevolution Linear Genetic Programming Surrogate-assisted Evolutionary Algorithms

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Underwater Salient Object Detection Based on Swintransformer 5th

Underwater Salient Object Detection Based on Swintransformer

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5th China Intelligent Robotics Academic Conference

作者： Jiao, Zhan Wang, Ruizi Fu, Bo Zhang, Tianzhuang Zhang, Ning Liaoning Vocat Coll Light Ind Dalian 116100 Peoples R China Liaoning Normal Univ Sch Comp Sci & Artificial Intelligence Dalian 116081 Peoples R China Northeast Normal Univ Training Ctr Minist Educ Studying Overseas Changchun Peoples R China

ISBN: (纸本)9789819616138;9789819616145

Underwater Salient Object Detection (USOD) has emerged as a specialized division of Salient Object Detection (SOD) to meet the increasing demand for underwater exploration. However, two major challenges hinder its development. First, current USOD datasets are limited in size and diversity, making them insufficient for robust model training and evaluation. Second, most existing deep learning-based USOD approaches rely on convolutional encoder-decoder architectures, which improve inference over traditional methods but still suffer from limited receptive fields and high computational costs. To address these challenges, we introduce a new USOD method based on the Swin transformer, which incorporates a multimodal feature fusion module to increase detection accuracy. Our model uses RGB images and depth maps to capture both semantic information and visual details. The multimodal feature fusion module dynamically adjusts feature importance through attention mechanisms, enhancing the ability of the model to extract meaningful information. By using a Swin transformer model with pretrained weights as the encoder backbone, the proposed method mitigates data scarcity issues and captures both the global context and long-range dependencies. The experimental results demonstrate that our approach achieves significant improvements in detecting salient objects in underwater environments.

关键词： Underwater image Salient object detection Swin transformer

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Towards Propositional KLM-Style Defeasible Standpoint Logics 5th

Towards Propositional KLM-Style Defeasible Standpoint Logics

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5th Southern African Conference for Artificial Intelligence Research

作者： Leisegang, Nicholas Meyer, Thomas Rudolph, Sebastian Univ Cape Town Cape Town South Africa CAIR Cape Town South Africa Tech Univ Dresden Dresden Germany Ctr Scalable Data Analyt & Artificial Intelligenc Dresden Germany

ISBN: (纸本)9783031782541;9783031782558

The KLM approach to defeasible reasoning introduces a weakened form of implication into classical logic. This allows one to incorporate exceptions to general rules into a logical system, and for old conclusions to be withdrawn upon learning new contradictory information. Standpoint logics are a group of logics, introduced to the field of Knowledge Representation in the last 5 years, which allow for multiple viewpoints to be integrated into the same ontology, even when certain viewpoints may hold contradicting beliefs. In this paper, we aim to integrate standpoints into KLM propositional logic in a restricted setting. We introduce the logical system of Defeasible Restricted Standpoint Logic (DRSL) and define its syntax and semantics. Specifically, we integrate ranked interpretations and standpoint structures, which provide the semantics for propositional KLM and propositional standpoint logic respectively, in order to introduce ranked standpoint structures for DRSL. Moreover, we extend the non-monotonic entailment relation of rational closure from the propositional KLM case to the DRSL case. The main contribution of this paper is to characterize rational closure for DRSL both algorithmically and semantically, showing that rational closure can be characterized through a single representative ranked standpoint structure. Finally, we conclude that the semantic and algorithmic characterizations of rational closure are equivalent, and that entailment-checking for DRSL under rational closure is in the same complexity class as entailment-checking for propositional KLM.

关键词： Knowledge representation Non-monotonic reasoning Defeasible reasoning Standpoint logic

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Design and Implementation of a Practice Record Visualization System Using Piano Performance Tracking Technology 1

引用

8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Mori, Haruna Sasaki, Mio Noto, Kaede Takegawa, Yoshinari Hirata, Keiji Future Univ Hakodate Sch Syst Informat Sci Hakodate Hokkaido Japan

ISBN: (数字)9783031826337

ISBN: (纸本)9783031826320;9783031826337

The purpose of this study is to develop a practice record visualization system using a piano performance tracking technology that utilizes gaze information. In general, piano lessons are held regularly, e.g., once a week, and the teacher observes the student's skills at a fixed point. However, it can be difficult for the teacher to fully understand and address all areas how the student has practiced from the previous lesson to the current lesson and need improvement. This makes it difficult to provide appropriate guidance in lessons, such as determining whether students are too nervous to perform well in front of the teacher, or whether they are also unable to perform well in home practice. To solve this problem, we propose a performance tracking algorithm that can handle keystroke errors and replaying, and a system that visualizes the amount of practice and other practice progress. The proposed system visualizes the amount of practice and errors in various units, such as notes and measures. To verify the usefulness of the proposed system, we conducted an evaluation experiment comparing the case of using the proposed system and not using the proposed system.

关键词： Visualization Teaching support Interactive system Eye tracking Performance error detection

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Support for Dynamic Social Cooperation 8th

Support for Dynamic Social Cooperation

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8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Faye, Pascal Francois Faye, Jeanne Ana Awa Senghor, Mariane Univ Sine Saloum El Hadj Ibrahima NIASS USSEIN Sing Sing Kaolack Senegal Univ Aix Marseille Inst Management Publ & Gouvernance Territoriale Marseille France

ISBN: (纸本)9783031838446;9783031838453

In many countries, agriculture is a means of development. Several structures are set up as cooperative, economic interest group (EIG), etc. However, these structures have very little interdependency that can allow them to go beyond their limits such as access to finance, access to national and international markets, etc.. This raises new challenges of collaboration between structures that we can consider each structure as a coalition. This work provides a coalition's migration (dynamic merging and splitting coalition) mechanism that allows auto-stable coalitions of self-interested agents in uncertainty context. Specifically, we assume uncertainties and interdependencies on tasks, agents and resources. We address the case in which agent and environment inherent uncertainties prohibit the computation of coalition stability ahead agent's goals. Facing such context, we propose a core-stable and auto-stabilizing anytime coalition formation mechanism which we denote as DMS (Dynamic Merging and Splitting). The mechanism arrives at a stability, maximizes social welfare, and converges gradually to near optimal results. DMS combines game theory methods and the laws of probability. Our experiments and their analysis demonstrate the efficiency of DMS.

关键词： Data analysis Multiagent Dynamic collaborations Coalition formation Negotiation

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IoT-Based Convolutional Neural Networks in a Farm Pest Detection Using Transfer Learning 5th

IoT-Based Convolutional Neural Networks in a Farm Pest Detec...

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5th International Conference on Computing science, Communication and Security

作者： Jani, Keyurbhai A. Chaubey, Nirbhay Kumar Panchal, Esan Tripathi, Pramod Yagnik, Shruti Gujarat Technol Univ Comp IT Engn Ahmadabad 382424 Gujarat India Ganpat Univ Comp Sci Mahesana 384012 Gujarat India Govt Polytech Informat Technol Gandhinagar 382027 Gujarat India Indus Univ Comp Engn Ahmadabad 382115 Gujarat India

ISBN: (纸本)9783031751691;9783031751707

In this study explores agriculture pest detection using transfer learning with IoT devices, evaluating VGG16, VGG19, Inception, and Xception CNN architectures with the agripest dataset. VGG16 and VGG19 show effective learning with consistent accuracy improvements. Inception V3 exhibits strong training but with variability in validation metrics, while Xception demonstrates robust performance and strong generalization to new data. The integrated system utilizes cameras, sensors, and drones for real-time image processing through a gateway and cloud server with a customized agripest dataset. Transfer learning generates a deployable.h5 file for pest identification. The generated custom model deployed on a gateway or server to classifies pests, alerting farmers through SMS, dashboard, or mobile app notifications. This synergy between machine learning and IoT offers rapid and precise pest detection in agriculture.

关键词： IoT deep learning CNN pest detection cloud farm gateway

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Elements to Address in a Computing Research Project Honours Course Module: A Tale of Two Universities 53rd

Elements to Address in a Computing Research Project Honours ...

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53rd Southern African computer Lecturers Association Meeting

作者： Smit, Imelda Barnard, Lynette Vogts, Dieter North West Univ Unit Data Sci & Comp Vanderbijlpark South Africa Nelson Mandela Univ Dept Comp Sci Gqeberha South Africa

ISBN: (纸本)9783031824777;9783031824784

Honours research projects are designed to help novice researchers to make the transition from being taught about and solving practical computing related problems, to doing research. The offering of the subject is unique in the sense that the conventional teaching model is not ideal;its needs are closer to a third-year capstone project module approach, but the situation is more complex and therefore needs special treatment. Typically, these subject modules are not a one-lecturer-does-everything-offering, because every student needs guidance to complete their project, and to support teaching in a wide variety of research specific topics. It makes more sense to include a small team of staff members to coordinate honours research projects, and to include academic staff as study leaders and topic specific experts. A compact, two-phase Design science Research method is utilised to allow a design-as-artefact for each entity under scrutiny, as the first phase. This approach accommodates each university as an alternative design. In the second phase, the design alternatives are tested by comparing the results from the alternatives obtained from the two cycles according to requirements. A third Design science Research cycle-for-demonstration extracts the best practice alternative design. Future research includes implementing the new design at the two participating universities. This paper also extends an invitation to other universities to implement the new design, and in doing so contribute to the debate and the improvement of future implementations.

关键词： Design science Research Computing Honours Research Project

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