Zobrazeno 1 - 10
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pro vyhledávání: '"Essay P"'
Autor:
Chowdhury, Shammur Absar, Almerekhi, Hind, Kutlu, Mucahid, Keles, Kaan Efe, Ahmad, Fatema, Mohiuddin, Tasnim, Mikros, George, Alam, Firoj
This paper presents a comprehensive overview of the first edition of the Academic Essay Authenticity Challenge, organized as part of the GenAI Content Detection shared tasks collocated with COLING 2025. This challenge focuses on detecting machine-gen
Externí odkaz:
http://arxiv.org/abs/2412.18274
Autor:
Yoshida, Lui
This study investigates the impact of example selection on the performance of au-tomated essay scoring (AES) using few-shot prompting with GPT models. We evaluate the effects of the choice and order of examples in few-shot prompting on several versio
Externí odkaz:
http://arxiv.org/abs/2411.18924
Publikováno v:
JCAL, 35(1), 110-120 (2019)
Most MOOC platforms either use simple schemes for aggregating peer grades, e.g., taking the mean or the median, or apply methodologies that increase students' workload considerably, such as calibrated peer review. To reduce the error between the inst
Externí odkaz:
http://arxiv.org/abs/2412.13348
The manual assessment and grading of student writing is a time-consuming yet critical task for teachers. Recent developments in generative AI, such as large language models, offer potential solutions to facilitate essay-scoring tasks for teachers. In
Externí odkaz:
http://arxiv.org/abs/2411.16337
Autor:
Riva, Davide, Rossetti, Cristina
In this essay we discuss the recent trends in visual analysis and exploration of Knowledge Graphs, particularly in conjunction with Knowledge Graph Embedding techniques. We present an overview of the current state of visualization techniques and fram
Externí odkaz:
http://arxiv.org/abs/2412.05289
Existing automated essay scoring (AES) has solely relied on essay text without using explanatory rationales for the scores, thereby forgoing an opportunity to capture the specific aspects evaluated by rubric indicators in a fine-grained manner. This
Externí odkaz:
http://arxiv.org/abs/2410.14202
Autor:
Maliha, Maisha, Pramanik, Vishal
Automatic essay grading (AEG) has attracted the the attention of the NLP community because of its applications to several educational applications, such as scoring essays, short answers, etc. AEG systems can save significant time and money when gradi
Externí odkaz:
http://arxiv.org/abs/2410.09319
Argumentative essay generation (AEG) aims to generate complete texts on specific controversial topics or debates. Although current AEG methods can generate individual opinions, they often overlook the high-level connections between these opinions. Th
Externí odkaz:
http://arxiv.org/abs/2410.22642
Autor:
Kundu, Anindita, Barbosa, Denilson
We evaluate the effectiveness of Large Language Models (LLMs) in assessing essay quality, focusing on their alignment with human grading. More precisely, we evaluate ChatGPT and Llama in the Automated Essay Scoring (AES) task, a crucial natural langu
Externí odkaz:
http://arxiv.org/abs/2409.13120
Autor:
Philip, Haddad, Tashu, Tsegaye Misikir
Automatic Essay Scoring (AES) is widely used to evaluate candidates for educational purposes. However, due to the lack of representative data, most existing AES systems are not robust, and their scoring predictions are biased towards the most represe
Externí odkaz:
http://arxiv.org/abs/2409.04795