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Found 4 papers, 1 papers with code
The Role of Complex NLP in Transformers for Text Ranking?
Even though term-based methods such as BM25 provide strong baselines in ranking, under certain conditions they are dominated by large pre-trained masked language models (MLMs) such as BERT.
How Different are Pre-trained Transformers for Text Ranking?
Our results contribute to our understanding of (black-box) neural rankers relative to (well-understood) traditional rankers, help understand the particular experimental setting of MS-Marco-based test collections.
On the Realization of Compositionality in Neural Networks
We present a detailed comparison of two types of sequence to sequence models trained to conduct a compositional task.
Point-less: More Abstractive Summarization with Pointer-Generator Networks
The Pointer-Generator architecture has shown to be a big improvement for abstractive summarization seq2seq models.
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