Dataset · Hugging Face

FutureMa/EvasionBench

Name: EvasionBench
Creator: FutureMa
License: apache-2.0
Keywords: benchmark:official, benchmark:eval-yaml, task_categories:text-classification, language:en, license:apache-2.0, size_categories:10K<n<100K, format:parquet, modality:text, library:datasets, library:pandas, library:polars, library:mlcroissant, arxiv:2601.09142, region:us, finance

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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Author / organization	FutureMa
License (as declared)	apache-2.0
Downloads	433 (as reported by Hugging Face)
Likes	111
Created	4 February 2026
Last updated at source	19 February 2026

financeearnings-callsevasion-detectionnlp

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Connected in the knowledge graph

mradermacher/Eva-4B-V2-GGUFModel · used to train
mradermacher/Eva-4B-V2-i1-GGUFModel · used to train
FutureMa/Eva-4B-V2Model · used to train

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