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Found 3 papers, 2 papers with code
Learning with Rejection for Abstractive Text Summarization
State-of-the-art abstractive summarization systems frequently hallucinate content that is not supported by the source document, mainly due to noise in the training dataset.
Learning Efficient Task-Specific Meta-Embeddings with Word Prisms
Word embeddings are trained to predict word cooccurrence statistics, which leads them to possess different lexical properties (syntactic, semantic, etc.)
An ensemble learning framework based on group decision making
The classification problem is a significant topic in machine learning which aims to teach machines how to group together data by particular criteria.
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