Improving truthfulness of headline generation
Witryna20 mar 2024 · We introduce a new task of entailment-relation-aware paraphrase generation and propose a RL-based weakly-supervised model ( ERAP) that can be trained without a task-specific corpus. Additionally, an existing NLI corpora is recasted to curate a small annotated dataset for this task, and provide performance bounds for it. 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. 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.
WitrynaDatasets created in the paper "Improving Truthfulness of Headline Generation" - headline-entailment/README.md at master · nlp-titech/headline-entailment 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.
Witryna1 dzień temu · Improving Truthfulness of Headline Generation Kazuki Matsumaru Sho Takase Naoaki Okazaki Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics pdf bib abs Enhancing Machine Translation with Dependency-Aware Self-Attention Emanuele Bugliarello Naoaki Okazaki Witryna1 lip 2024 · Most studies on abstractive summarization report ROUGE scores between system and reference summaries. However, we have a concern about the …
Witrynaheadline-entailment Datasets created in the paper Improving Truthfulness of Headline Generation. Gigaword Entailment Dataset We put datasets of annotation results we …
Witryna2 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... list of cuv vehiclesWitrynaThis paper explores improving the truthfulness in headline generation on two popular datasets. Analyzing headlines generated by the state-of-the-art encoder-decoder … image tag in ionichttp://sidenoter.nii.ac.jp/acl_anthology/2024.acl-main.123/ image tag for cssWitrynaThe 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 … list of cvc compound wordsWitrynaThispaper 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... image tag in html in vs codeWitryna1 sty 2024 · Usually, headline generation is regarded as a special task of general abstractive text summarization, and the majority of existing studies could be easily … list of cvn carriersWitrynaImproving 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 image tag format in html