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20242026
most citedPrompting open-source and commercial language models for grammatical error correction of English learner text

10 citations · 11 across the 8 of their papers we have counts for

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cs.AI2024

StateAct: Enhancing LLM Base Agents via Self-prompting and State-tracking

Nikolai Rozanov, Marek Rei

Large language models (LLMs) are increasingly used as autonomous agents, tackling tasks from robotics to web navigation. Their performance depends on the underlying base agent. Exi…

cs.CL2024

DiffuseDef: Improved Robustness to Adversarial Attacks via Iterative Denoising

Zhenhao Li, Huichi Zhou, Marek Rei +1

Pretrained language models have significantly advanced performance across various natural language processing tasks. However, adversarial attacks continue to pose a critical challe…

cs.CL2024★ 10 cited

Prompting open-source and commercial language models for grammatical error correction of English learner text

Christopher Davis, Andrew Caines, Øistein Andersen +6

Thanks to recent advances in generative AI, we are able to prompt large language models (LLMs) to produce texts which are fluent and grammatical. In addition, it has been shown tha…