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Found 5 papers, 3 papers with code
Uncovering Factor Level Preferences to Improve Human-Model Alignment
Our factor level analysis reveals a substantial discrepancy between human and LLM preferences in generation tasks, whereas LLMs show strong alignment with human preferences in evaluation tasks.
The Generative AI Paradox on Evaluation: What It Can Solve, It May Not Evaluate
This paper explores the assumption that Large Language Models (LLMs) skilled in generation tasks are equally adept as evaluators.
KOLD: Korean Offensive Language Dataset
Recent directions for offensive language detection are hierarchical modeling, identifying the type and the target of offensive language, and interpretability with offensive span annotation and prediction.
KLUE: Korean Language Understanding Evaluation
We introduce Korean Language Understanding Evaluation (KLUE) benchmark.
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