CNN/DailyMail
A dataset constructed from news articles sourced from CNN and the Daily Mail. It is extensively used for training and evaluating models on abstractive and extractive text summarization as well as reading comprehension tasks, and serves as a standard benchmark in natural language processing.
Timeline (last 90 days)
In next-word prediction comparison experiments on the CNN/DailyMail dataset, ILRN and Transformer each had about 532K parameters, were each trained on 20 million next-word targets, and were trained independently under two context windows of 96 and 256.
The study validates on three datasets—TinyStories, WikiText-103, and CNN/DailyMail—scaling each corpus from 512 chunks to 2,048 chunks, with each chunk consisting of 64 tokens.
All Facts (2)
In next-word prediction comparison experiments on the CNN/DailyMail dataset, ILRN and Transformer each had about 532K parameters, were each trained on 20 million next-word targets, and were trained independently under two context windows of 96 and 256.
50%UnverifiedThe study validates on three datasets—TinyStories, WikiText-103, and CNN/DailyMail—scaling each corpus from 512 chunks to 2,048 chunks, with each chunk consisting of 64 tokens.
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