{"id":"https://openalex.org/W7165643336","doi":"https://doi.org/10.48550/arxiv.2606.22079","title":"Where Does the Signal Live? A Web Data Recipe for Medical Encoder Pretraining","display_name":"Where Does the Signal Live? A Web Data Recipe for Medical Encoder Pretraining","publication_year":2026,"publication_date":"2026-06-20","ids":{"openalex":"https://openalex.org/W7165643336","doi":"https://doi.org/10.48550/arxiv.2606.22079"},"language":"en","primary_location":{"id":"pmh:oai:HAL:hal-05685251v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05685251","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2026","raw_type":"info:eu-repo/semantics/preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-05685251","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135304882","display_name":"Bofeng Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Bofeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139180811","display_name":"Jacques Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Jacques","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075501154","display_name":"Diane Bouchacourt","orcid":"https://orcid.org/0009-0001-9078-8836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bouchacourt, Diane","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049759128","display_name":"Nicolas Barascud","orcid":"https://orcid.org/0000-0003-1495-561X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barascud, Nicolas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139134625","display_name":"Fajwel Fogel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fogel, Fajwel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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":false,"primary_topic":{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.20360000431537628,"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":0.20360000431537628,"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":0.19920000433921814,"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":0.12620000541210175,"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/recipe","display_name":"Recipe","score":0.6682000160217285},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6608999967575073},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5680999755859375},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5593000054359436},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.550599992275238},{"id":"https://openalex.org/keywords/web-application","display_name":"Web application","score":0.5026000142097473},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4584999978542328},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.45210000872612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7717000246047974},{"id":"https://openalex.org/C2778671685","wikidata":"https://www.wikidata.org/wiki/Q219239","display_name":"Recipe","level":2,"score":0.6682000160217285},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6608999967575073},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5680999755859375},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5593000054359436},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.550599992275238},{"id":"https://openalex.org/C118643609","wikidata":"https://www.wikidata.org/wiki/Q189210","display_name":"Web application","level":2,"score":0.5026000142097473},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5006999969482422},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4562999904155731},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.45210000872612},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.41190001368522644},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3840000033378601},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.335099995136261},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3190000057220459},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2912999987602234},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.2858999967575073},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.28139999508857727},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26750001311302185},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:HAL:hal-05685251v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05685251","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2026","raw_type":"info:eu-repo/semantics/preprint"},{"id":"doi:10.48550/arxiv.2606.22079","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22079","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-05685251v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05685251","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2026","raw_type":"info:eu-repo/semantics/preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8553087115287781}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Web":[0],"data":[1,47,138],"curation":[2,48],"has":[3],"been":[4],"widely":[5],"studied":[6],"for":[7,15],"decoder":[8],"Large":[9],"Language":[10,53],"Model":[11],"(LLM)":[12],"pretraining.":[13],"Encoders":[14],"dense-terminology":[16,58],"domains":[17],"such":[18],"as":[19],"medicine,":[20],"by":[21],"contrast,":[22],"are":[23],"pretrained":[24],"on":[25,100,114,128,161],"small,":[26],"manually-curated":[27],"corpora":[28],"that":[29],"limit":[30],"scalability":[31],"and":[32,118,132,152,167],"writing":[33],"style":[34],"diversity,":[35],"a":[36,57,147,154,168],"bottleneck":[37],"even":[38],"more":[39],"severe":[40],"in":[41,56,78],"non-English":[42],"clinical":[43,170],"settings.":[44],"Whether":[45],"web-scale":[46],"also":[49],"benefits":[50],"encoder":[51,158],"Masked":[52],"Modeling":[54],"(MLM)":[55],"domain":[59],"remains":[60],"an":[61,84],"open":[62],"question.":[63],"To":[64],"address":[65],"this,":[66],"we":[67],"introduce":[68],"two":[69,120],"complementary":[70],"levers.":[71],"Medical-term":[72],"density":[73,106],"filtering":[74],"selects":[75],"documents":[76,88],"rich":[77],"medical":[79,102,116,149,157],"terms.":[80],"Signal-amplifying":[81,124],"rephrasing":[82,125],"uses":[83],"LLM":[85],"to":[86],"rewrite":[87],"into":[89],"denser":[90],"variants":[91],"with":[92,135],"broader":[93],"entity":[94],"contexts.":[95],"We":[96],"instantiate":[97],"the":[98,109,119,140,163],"recipe":[99,144],"French":[101,148,156],"NLP.":[103],"The":[104,143],"medical-term":[105],"filter":[107,113],"outperforms":[108],"widely-used":[110],"educational":[111],"quality":[112],"downstream":[115],"tasks,":[117],"complement":[121],"each":[122],"other.":[123],"alone":[126],"improves":[127],"raw":[129],"web":[130,137],"data,":[131],"mixing":[133],"it":[134],"filtered":[136],"produces":[139],"largest":[141],"gain.":[142],"yields":[145],"FineMed,":[146],"pretraining":[150],"corpus,":[151],"DoctoBERT,":[153],"state-of-the-art":[155],"family":[159],"evaluated":[160],"both":[162],"public":[164],"benchmark":[165],"DrBenchmark":[166],"proprietary":[169],"Named":[171],"Entity":[172],"Recognition":[173],"(NER)":[174],"task.":[175]},"counts_by_year":[],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2026-06-24T00:00:00"}