LLMs show practical but imperfect ability to replicate human annotations of language ideologies in Luxembourgish comments, with some gains from machine translation to high-resource languages.
Therefore, we adopt prompt 4 as the final prompting template for all further experiments
2 Pith papers cite this work. Polarity classification is still indexing.
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Ctx2Skill uses a self-evolving multi-agent loop with Challenger, Reasoner, Judge, and Cross-time Replay to discover context-specific skills, improving task-solving rates on CL-bench benchmarks across models.
citing papers explorer
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Language Ideologies in a Multilingual Society: An LLM-based Analysis of Luxembourgish News Comments
LLMs show practical but imperfect ability to replicate human annotations of language ideologies in Luxembourgish comments, with some gains from machine translation to high-resource languages.
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From Context to Skills: Can Language Models Learn from Context Skillfully?
Ctx2Skill uses a self-evolving multi-agent loop with Challenger, Reasoner, Judge, and Cross-time Replay to discover context-specific skills, improving task-solving rates on CL-bench benchmarks across models.