Papers with dataset adaptation

3 papers
The AI Committee: A Multi-Agent Framework for Automated Validation and Remediation of Web-Sourced Data (2026.eacl-demo)

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Challenge: largelanguage models (LLMs)-powered web agents can be useful for research in areas such as social science, public health, and economics.
Approach: They propose a model-agnostic multi-agent system that auto-mates the process of validating and remediatingweb-sourced datasets.
Outcome: The proposed system outperforms baseline approaches and achieves datacompleteness and precision up to 73.3%.
Guiding Medical Vision-Language Models with Diverse Visual Prompts: Framework Design and Comprehensive Exploration of Prompt Variations (2025.naacl-long)

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Challenge: Current vision-language models lack the ability to focus on specific areas designated by humans . a new framework that integrates medical entity extraction, visual prompt generation, and dataset adaptation is proposed to improve visual prompt-guided fine-tuning.
Approach: They propose to use visual prompts to guide and enhance formation of region-specific attention.
Outcome: The proposed framework outperforms state-of-the-art large vision-language models on medical datasets.
Diversity in Unity, Theory in Practice: Hierarchical Multitask Benchmarks for Chinese Minority Languages (2026.acl-long)

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Challenge: CMiLBench is a framework to evaluate linguistically and culturally diverse minority languages . rapid evolution of LLMs has revolutionized NLP, but progress is unevenly distributed .
Approach: They propose a framework to translate a theoretical notion of "diversity in unity" into practical evaluation for three minority languages . CMiLBench comprises 24,663 instances across 5 difficulty levels and 17 tasks .
Outcome: The proposed framework evaluates 14 state-of-the-art LLMs with a hybrid framework . it integrates automatic metrics and LLM-as-a-Judge scoring .

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