{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T14:47:36Z","timestamp":1773326856591,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684369","type":"print"},{"value":"9781643684376","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T00:00:00Z","timestamp":1695859200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,28]]},"abstract":"<jats:p>Multiple business scenarios require an automated generation of descriptive human-readable long text from structured input data, where the source is typically a high-resource language and the target is a low or medium resource language. We define the Cross-Lingual Fact to Long Text Generation (XFLT) as a novel natural language generation (NLG) task that involves generating descriptive and human-readable long text in a target language from structured input data (such as fact triples) in a source language. XFLT is challenging because of (a) hallucinatory nature of the state-of-the-art NLG models, (b) lack of good quality training data, and (c) lack of a suitable cross-lingual NLG metric. Unfortunately previous work focuses on different related problem settings (cross-lingual facts to short text or monolingual graph to text) and has made no efforts to handle hallucinations. In this paper, we contribute a novel dataset, XLALIGN with over 64,000 paragraphs across 12 different languages, and English facts. We propose a novel solution to the XFLT task which addresses these challenges by training multilingual Transformer-based encoder-decoder models with coverage prompts and grounded decoding. Further, it improves on the XFLT quality by defining task-specific reward functions and training on them using reinforcement learning. On XLALIGN, we compare this novel solution with several strong baselines using a new metric, cross-lingual PARENT. We also make our code and data publicly available https:\/\/drive.google.com\/file\/d\/1sHgcwXKribjrm2grbs-LzXUUqXQitD2N\/.<\/jats:p>","DOI":"10.3233\/faia230512","type":"book-chapter","created":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:19:03Z","timestamp":1695979143000},"source":"Crossref","is-referenced-by-count":1,"title":["XFLT: Exploring Techniques for Generating Cross Lingual Factually Grounded Long Text"],"prefix":"10.3233","author":[{"given":"Bhavyajeet","family":"Singh","sequence":"first","affiliation":[{"name":"IIIT Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aditya","family":"Hari","sequence":"additional","affiliation":[{"name":"IIIT Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rahul","family":"Mehta","sequence":"additional","affiliation":[{"name":"IIIT Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tushar","family":"Abhishek","sequence":"additional","affiliation":[{"name":"IIIT Hyderabad, India"},{"name":"Microsoft"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manish","family":"Gupta","sequence":"additional","affiliation":[{"name":"IIIT Hyderabad, India"},{"name":"Microsoft"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vasudeva","family":"Varma","sequence":"additional","affiliation":[{"name":"IIIT Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2023"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230512","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:19:05Z","timestamp":1695979145000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230512"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,28]]},"ISBN":["9781643684369","9781643684376"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230512","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,28]]}}}