Papers with optimizing

2 papers
ITERATE: Image-Text Enhancement, Retrieval, and Alignment for Transmodal Evolution with LLMs (2025.coling-main)

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Challenge: a new framework for visual annotation of text-based questions is needed to improve performance . obtaining corresponding images through manual annotation often entails high costs .
Approach: They propose a framework that uses visual modality to enhance the performance of text-based questions.
Outcome: The proposed framework improves the alignment between text and images by using search engines or web scraping techniques.
The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm (2024.emnlp-main)

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Challenge: Existing approaches to safety alignment focus on homogeneous monolingual settings . preference training and safety measures often overfit to harms common in Western-centric datasets .
Approach: They propose to use human annotated red teaming prompts to identify global and local harms.
Outcome: The proposed approach can address and optimize for a non-homogeneous set of languages and cultural preferences while minimizing both global and local harms.

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