LLM tutors leak answers under adversarial student attacks, but a fine-tuned jailbreak agent and simple defenses can benchmark and improve robustness.
(Eds.), Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics, Vienna, Austria
3 Pith papers cite this work, alongside 2 external citations. Polarity classification is still indexing.
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Copa is a theory-guided multimodal LLM agent that supports high school computational modeling through adaptive feedback, shown in a 33-dyad study to increase student confidence and conceptual verbalization without fostering dependence.
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