Papers with MSoR.

1 papers
Can Many-Shot In-Context Learning Help LLMs as Evaluators? A Preliminary Empirical Study (2025.coling-main)

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Challenge: Existing evaluation approaches to evaluate Large Language Models are affected by potential biases within LLMs.
Approach: They propose two many-shot In-Context Learning (ICL) prompt templates to help LLM evaluators mitigate potential biases.
Outcome: The proposed templates reduce biases by using in-context examples with model-generated rationales as references.

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