Bandit-driven prompt selection for low-cost LLM essay scoring reduces inference costs in AES by adapting prompts via a multi-armed bandit controller
Read the original at arxiv.org→arXiv:2608.23814v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate strong capabilities in automated essay scoring (AES), but contemporary approaches typically employ fixed prompt selection,...
Original headline: "Learning to Grade Efficiently: A Bandit-Driven Prompt-Selection Framework for Low-Cost LLM Essay Scoring"
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- Aug 26, 04:00 UTC arXiv cs.LG lead source Learning to Grade Efficiently: A Bandit-Driven Prompt-Selection Framework for Low-Cost LLM Essay Scoring