What is my essay really saying? Using extractive summarization to mo- tivate reflection and redrafting. In: Proceedings of the Workshops at the 16th International Conference on Artificial Intelligence in Education AIED 2013, Memphis, USA, July 9-13. Vol. 1009 of CEUR Workshop Proceedings. CEUR...
Summarization is a preconfigured feature that uses extractive text summarization to produce a summary of documents and conversation transcriptions. It extracts sentences that collectively represent the most important or relevant information within the original content. Key phrase extraction Key phrase extraction...
Prompt: Summarize the text – Text summarization can be implemented using machine learning models, natural language processing techniques, and algorithms designed to evaluate the importance of sentences or phrases within a text. The choice between extractive and abstractive summarization depends on the spe...
aExtractive speech summarization using structural modeling 可提取讲话总结使用结构塑造 [translate] aThe model groups’ similar communication functions into one of seven logical layers. A layer serves the layer above it and is served by the layer below it. For example, a layer that provides error-...
which is then used to condition the transformer language model on relevant information before being tasked with generating a summary. We show that this extractive step significantly improves summarization results. We also show that this approach produces more abstractive summaries compared to prior work ...
most state-of-the-art results on language generation tasks are attained using beam search despite its overwhelmingly high search error rate. This implies that the MAP objective alone does not express the properties we desire in text, which merits the question: if beam search is the answer, wha...
Linux. And again, that all started in the early, mid aughts. And you can see now that again, about 12 years later, this is really becoming commodified. And that's moving forward, I'll talk more. But that space of hardware in the cloud is really changing rapidly, and it'...
As we close out 2020, there is much to look forward to in the upcoming year within the NLP space. Two key areas will stand out in terms of value, usage, and ROI: natural language generation (NLG) and an improved customization experience. Natural Language Generation: NLG (which we explored...
The first thing is Big Data, and the next is Big Compute, and the third is Big Models. To give you a little bit of background, big data really started out in Q3 of 1997. There were four teams that were struggling with the same problem. It was what would become Google, Yahoo...