Knowledge-Based and Generative-AI-Driven Pedagogical Conversational Agents: A Comparative Study of Grice’s Cooperative Principles and Trust

Wölfel, Matthias; Shirzad, Mehrnoush Barani; Reich, Andreas; Anderer, Katharina

doi:10.3390/bdcc8010002

Cited by 2 publications

(1 citation statement)

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“…However, ChatGPT is not only an expansion of existing models. It has been distinctly refined and enhanced through a process involving supervised and reinforcement learning methods informed by human feedback [16,17]. Representing a groundbreaking advancement in NLP, it has become the first model to be embraced beyond NLP research, and it is adept at producing text closely resembling human writing [18].…”

Section: Large Language Modelsmentioning

confidence: 99%

AI-Generated Text Detector for Arabic Language Using Encoder-Based Transformer Architecture

Alshammari,

El-Sayed,

Elleithy

2024

BDCC

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The effectiveness of existing AI detectors is notably hampered when processing Arabic texts. This study introduces a novel AI text classifier designed specifically for Arabic, tackling the distinct challenges inherent in processing this language. A particular focus is placed on accurately recognizing human-written texts (HWTs), an area where existing AI detectors have demonstrated significant limitations. To achieve this goal, this paper utilized and fine-tuned two Transformer-based models, AraELECTRA and XLM-R, by training them on two distinct datasets: a large dataset comprising 43,958 examples and a custom dataset with 3078 examples that contain HWT and AI-generated texts (AIGTs) from various sources, including ChatGPT 3.5, ChatGPT-4, and BARD. The proposed architecture is adaptable to any language, but this work evaluates these models’ efficiency in recognizing HWTs versus AIGTs in Arabic as an example of Semitic languages. The performance of the proposed models has been compared against the two prominent existing AI detectors, GPTZero and OpenAI Text Classifier, particularly on the AIRABIC benchmark dataset. The results reveal that the proposed classifiers outperform both GPTZero and OpenAI Text Classifier with 81% accuracy compared to 63% and 50% for GPTZero and OpenAI Text Classifier, respectively. Furthermore, integrating a Dediacritization Layer prior to the classification model demonstrated a significant enhancement in the detection accuracy of both HWTs and AIGTs. This Dediacritization step markedly improved the classification accuracy, elevating it from 81% to as high as 99% and, in some instances, even achieving 100%.

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Section: Large Language Modelsmentioning

confidence: 99%

AI-Generated Text Detector for Arabic Language Using Encoder-Based Transformer Architecture

Alshammari,

El-Sayed,

Elleithy

2024

BDCC

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Framework for Integrating Generative AI in Developing Competencies for Accounting and Audit Professionals

Anica-Popa,

Vrîncianu,

Anica-Popa

et al. 2024

Electronics

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The study aims to identify the knowledge, skills and competencies required by accounting and auditing (AA) professionals in the context of integrating disruptive Generative Artificial Intelligence (GenAI) technologies and to develop a framework for integrating GenAI capabilities into organisational systems, harnessing its potential to revolutionise lifelong learning and skills development and to assist day-to-day operations and decision-making. Through a systematic literature review, 103 papers were analysed, to outline, in the current business ecosystem, the competencies’ demand generated by AI adoption and, in particular, GenAI and its associated risks, thus contributing to the body of knowledge in underexplored research areas. Positioned at the confluence of accounting, auditing and GenAI, the paper introduces a meaningful overview of knowledge in the areas of effective data analysis, interpretation of findings, risk awareness and risk management. It emphasizes and reshapes the role of required skills for accounting and auditing professionals in discovering the true potential of GenAI and adopting it accordingly. The study introduces a new LLM-based system model that can enhance its GenAI capabilities through collaboration with similar systems and provides an explanatory scenario to illustrate its applicability in the accounting and audit area.

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Knowledge-Based and Generative-AI-Driven Pedagogical Conversational Agents: A Comparative Study of Grice’s Cooperative Principles and Trust

Cited by 2 publications

References 50 publications

AI-Generated Text Detector for Arabic Language Using Encoder-Based Transformer Architecture

AI-Generated Text Detector for Arabic Language Using Encoder-Based Transformer Architecture

Framework for Integrating Generative AI in Developing Competencies for Accounting and Audit Professionals

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