FutureMa/EvasionBench
EvasionBench EvasionBench is a benchmark dataset for detecting evasive answers in earnings call Q&A sessions. The task is to classify how directly corporate management addresses questions from financial analysts. Dataset Summary This dataset contains 16,726 question-answer pairs from earnings call transcripts, each labeled with one of three evasion levels. The labels were generated using the Eva-4B-V2 model, a fine-tuned classifier specifically… See the full description on the dataset page: https://huggingface.co/datasets/FutureMa/EvasionBench.
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