{"id":"https://openalex.org/W7102411047","doi":"https://doi.org/10.48550/arxiv.2510.24365","title":"Text Simplification with Sentence Embeddings","display_name":"Text Simplification with Sentence Embeddings","publication_year":2025,"publication_date":"2025-10-28","ids":{"openalex":"https://openalex.org/W7102411047","doi":"https://doi.org/10.48550/arxiv.2510.24365"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2510.24365","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.24365","pdf_url":"https://arxiv.org/pdf/2510.24365","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.24365","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035746903","display_name":"Matthew Shardlow","orcid":"https://orcid.org/0000-0003-1129-2750","observed_orcids":["https://orcid.org/0000-0003-1129-2750"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shardlow, Matthew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5035746903"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.9272000193595886,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.9272000193595886,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.06560000032186508,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.0012000000569969416,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/text-simplification","display_name":"text simplification","score":0.9980000257492065},{"id":"https://openalex.org/keywords/sentence-embeddings","display_name":"sentence embeddings","score":1.0},{"id":"https://openalex.org/keywords/text-complexity","display_name":"text complexity","score":0.8100000023841858},{"id":"https://openalex.org/keywords/feedforward-neural-networks","display_name":"feedforward neural networks","score":0.6029999852180481},{"id":"https://openalex.org/keywords/low-resource-languages","display_name":"low-resource languages","score":0.5740000009536743},{"id":"https://openalex.org/keywords/natural-language-generation","display_name":"natural language generation","score":0.6349999904632568}],"concepts":[{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7735999822616577},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7421000003814697},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6725000143051147},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6480000019073486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6446999907493591},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6176000237464905},{"id":"https://openalex.org/C59415355","wikidata":"https://www.wikidata.org/wiki/Q3484781","display_name":"Text simplification","level":3,"score":0.5490999817848206},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5303999781608582},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4618000090122223},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.42579999566078186},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.3529999852180481},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.328900009393692},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.3230000138282776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.2554999887943268},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25440001487731934},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.25049999356269836}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.24365","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.24365","pdf_url":"https://arxiv.org/pdf/2510.24365","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2510.24365","doi":"https://doi.org/10.48550/arxiv.2510.24365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.24365","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.24365","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.24365","pdf_url":"https://arxiv.org/pdf/2510.24365","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Quality education","score":0.8136758804321289,"id":"https://metadata.un.org/sdg/4"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Sentence":[0],"embeddings":[1,30,50],"can":[2],"be":[3],"decoded":[4],"to":[5,13,43,59,82,118,122],"give":[6],"approximations":[7],"of":[8,23,79],"the":[9,21,77,95,120],"original":[10],"texts":[11],"used":[12],"create":[14],"them.":[15],"We":[16,34,56,99],"explore":[17],"this":[18],"effect":[19],"in":[20,68,104],"context":[22],"text":[24,29,129],"simplification,":[25],"demonstrating":[26],"that":[27,101],"reconstructed":[28],"preserve":[31],"complexity":[32],"levels.":[33],"experiment":[35],"with":[36],"a":[37,46,60,109],"small":[38],"feed":[39],"forward":[40],"neural":[41],"network":[42],"effectively":[44],"learn":[45],"transformation":[47,81],"between":[48],"sentence":[49,105],"representing":[51],"high-complexity":[52],"and":[53,62,115,131],"low-complexity":[54],"texts.":[55],"provide":[57],"comparison":[58],"Seq2Seq":[61],"LLM-based":[63],"approach,":[64],"showing":[65],"encouraging":[66],"results":[67],"our":[69,80],"much":[70],"smaller":[71],"learning":[72,102],"setting.":[73],"Finally,":[74],"we":[75],"demonstrate":[76],"applicability":[78],"an":[83],"unseen":[84],"simplification":[85,130],"dataset":[86],"(MedEASI),":[87],"as":[88,90],"well":[89],"datasets":[91],"from":[92],"languages":[93],"outside":[94],"training":[96],"data":[97],"(ES,DE).":[98],"conclude":[100],"transformations":[103],"embedding":[106],"space":[107],"is":[108],"promising":[110],"direction":[111],"for":[112,128],"future":[113],"research":[114],"has":[116],"potential":[117],"unlock":[119],"ability":[121],"develop":[123],"small,":[124],"but":[125],"powerful":[126],"models":[127],"other":[132],"natural":[133],"language":[134],"generation":[135],"tasks.":[136]},"counts_by_year":[],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2025-10-30T00:00:00"}
