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Found 2 papers, 2 papers with code
Investigating Multi-source Active Learning for Natural Language Inference
We show that four popular active learning schemes fail to outperform random selection when applied to unlabelled pools comprised of multiple data sources on the task of natural language inference.
[Re] Reproducing Learning to Deceive With Attention-Based Explanations
Across multiple datasets, the authors show that with the impermissible tokens removed the model accuracy drops, implying their usage in prediction.
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