Witryna5 Improving the truthfulness of models 5.1 Headline generation models 5.2 Data preparation WitrynaThis paper explores improving the truthfulness in headline generation on two popular datasets. Analyzing headlines generated by the state-of-the-art encoder-decoder model, we show that the model sometimes generates untruthful headlines. We conjecture that one of the reasons lies in untruthful supervision data used for training the model.

Improving Truthfulness of Headline Generation - 百度学术

WitrynaThis paper explores improving the truthfulness in headline generation on two popular datasets. Analyzing headlines generated by the state-of-the-art encoder-decoder … WitrynaImproving Truthfulness of Headline Generation Most studies on abstractive summarization report ROUGE scores between system and reference summaries. … cisco telephony training

[2005.00882v1] Improving Truthfulness of Headline Generation

WitrynaImproving Truthfulness of Headline Generation - CORE Reader Witryna1 lip 2024 · Most studies on abstractive summarization report ROUGE scores between system and reference summaries. However, we have a concern about the truthfulness of ge... WitrynaWe introduce FunLines, a competitive game where players edit news headlines to make them funny, and where they rate the funniness of headlines edited by others. FunLines makes the humor generation process fun, interactive, collaborative, rewarding and educational, keeping players engaged and providing humor data at a very low cost … diamonds offered