The LLMBar-Select dataset is a curated subset of the original LLMBar dataset introduced by Zeng et al. (2024). The LLMBar dataset consists of 419 instances, each containing an instruction paired with two outputs: one that faithfully follows the instruction and another that deviates while presenting superficially appealing qualities. It is designed to evaluate LLM-based evaluators more rigorously and objectively than previous benchmarks.… See the full description on the dataset page: https://huggingface.co/datasets/bay-calibration-llm-evaluators/llmbar-annotated-latest.
