KaLM-Reranker-V1 introduces a fast but not late-interaction reranker that decouples passage pre-encoding from query processing via encoder-decoder architecture and cross-attention to achieve efficiency and competitive performance.
DRCD: a Chinese Machine Reading Comprehension Dataset
3 Pith papers cite this work. Polarity classification is still indexing.
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abstract
In this paper, we introduce DRCD (Delta Reading Comprehension Dataset), an open domain traditional Chinese machine reading comprehension (MRC) dataset. This dataset aimed to be a standard Chinese machine reading comprehension dataset, which can be a source dataset in transfer learning. The dataset contains 10,014 paragraphs from 2,108 Wikipedia articles and 30,000+ questions generated by annotators. We build a baseline model that achieves an F1 score of 89.59%. F1 score of Human performance is 93.30%.
verdicts
UNVERDICTED 3representative citing papers
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End-to-end Contrastive Language-Speech Pretraining Model For Long-form Spoken Question Answering
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