Improving truthfulness of headline generation
WitrynaThis paper explores improving the truthfulness in headline generation on two popular datasets. Analyzing headlines generated by the state-of-the-art encoder-decoder … 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
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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. This 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.
WitrynaThis paper explores improving the truthfulness in headline generation on two popular datasets. Analyzing headlines generated by the state-of-the-art encoder-decoder …
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. WitrynaHeadline generation 20 papers with code • 1 benchmarks • 1 datasets
WitrynaThe column “# words” presents two values for each row: a top value is the total number of words in the headline; and the bottom value is the total number of words in the …
Witryna1 前言. 本次介绍ACL2024年会议中开源的一个关于新闻标题生成的数据集——PENS，论文标题为。 这里需要提及的是：PENS数据集跟以往的不太一样（如Google News），它包含了用户信息（如阅读过的新闻，点击的次数等），这样利用该数据集 ... chain link bottle openerWitrynaIn this paper, we explore improving the truthful-ness in abstractive summarization on two datasets, English Gigaword and JApanese MUlti-Length Headline Corpus … chain link box hingeWitrynaThis paper explores improving the truthfulness in headline generation on two popular datasets. Analyzing headlines generated by the state-of-the-art encoder-decoder … chain link batting cageWitrynaACL2024: Improving Truthfulness of Headline Generation Improving Truthfulness of Headline Generation Kazuki Matsumaru , Sho Takase , Naoaki Okazaki Abstract … chain link braidWitryna2 maj 2024 · Thispaper explores improving the truthfulness inheadline generation on two popular datasets.Analyzing headlines generated by the state-of-the-art encoder-decoder model, we showthat the model sometimes generates untruthfulheadlines. We conjecture that one of the rea-sons lies in untruthful supervision data usedfor training … hap physician finderWitrynaImproving Truthfulness of Headline Generation URL Young researcher’s encouragement award, the 242nd Meeting of Special Interest Group of Natural Language Processing (SIGNL), Information Processing Society of Japan (IPSJ) (2024-10-25) Tatsuya Hiraoka HMM-based Neural Network Capturing Latent History with RNN URL chain link brace bandWitrynaThis 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. chainlink bonds