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Found 5 papers, 1 papers with code
Improved Performances and Motivation in Intelligent Tutoring Systems: Combining Machine Learning and Learner Choice
In this context, the ZPDES algorithm, based on the Learning Progress Hypothesis (LPH) and multi-armed bandit machine learning techniques, sequences exercises that maximize learning progress (LP).
GPT-3-driven pedagogical agents for training children's curious question-asking skills
In this context, we propose to leverage advances in the natural language processing field (NLP) and investigate the efficiency of using a large language model (LLM) for automating the production of the pedagogical content of a curious question-asking (QA) training.
Selecting Better Samples from Pre-trained LLMs: A Case Study on Question Generation
Large Language Models (LLMs) have in recent years demonstrated impressive prowess in natural language generation.
Language-biased image classification: evaluation based on semantic representations
This suggests that the semantic word representation in the CLIP visual processing is not shared with the image representation, although the word representation strongly dominates for word-embedded images.
Evaluating Language-biased image classification based on semantic compositionality
This suggests that the semantic word representation in the CLIP visual processing is not shared with the image representation, although the word representation strongly dominates for word-embedded images.
