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Found 4 papers, 0 papers with code
Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models
Abstractive summarization models often generate factually inconsistent content particularly when the parametric knowledge of the model conflicts with the knowledge in the input document.
Is Cross-modal Information Retrieval Possible without Training?
Embeddings for a particular modality of data occupy a high-dimensional space of its own, but it can be semantically aligned to another by a simple mapping without training a deep neural net.
Enhancing Semantic Understanding with Self-supervised Methods for Abstractive Dialogue Summarization
We build and fine-tune an abstractive dialogue summarization model on a shared encoder-decoder architecture using the enhanced BERT.
Abstractive Dialogue Summarization
Abstractive Text Summarization
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Adversarial Learning of Semantic Relevance in Text to Image Synthesis
Instead of selecting random training examples, we perform negative sampling based on the semantic distance from a positive example in the class.
