Papers by Amy X Zhang

1 papers
SPICA: Retrieving Scenarios for Pluralistic In-Context Alignment (2025.findings-acl)

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Challenge: In-context learning only considers similarity when drawing few-shot examples and not cross-group differences in values.
Approach: They propose a framework that accounts for group-level differences during in-context example retrieval by using scenario banks, group-informed retrieval metrics, and in-constraint alignment prompts.
Outcome: The proposed framework improves on an alignment task with groups seeing up to a +0.16 point improvement on a 5 point scale.

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