{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T16:38:36Z","timestamp":1772210316625,"version":"3.50.1"},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,23]]},"DOI":"10.1109\/icassp43922.2022.9746018","type":"proceedings-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T19:50:34Z","timestamp":1651089034000},"page":"1-5","source":"Crossref","is-referenced-by-count":9,"title":["Metricbert: Text Representation Learning Via Self-Supervised Triplet Training"],"prefix":"10.1109","author":[{"given":"Itzik","family":"Malkiel","sequence":"first","affiliation":[{"name":"Microsoft"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dvir","family":"Ginzburg","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oren","family":"Barkan","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Avi","family":"Caciularu","sequence":"additional","affiliation":[{"name":"Bar-Ilan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yoni","family":"Weill","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noam","family":"Koenigstein","sequence":"additional","affiliation":[{"name":"Microsoft"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Roberta: A robustly optimized bert pretraining approach","author":"liu","year":"2019"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.272"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5722"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.eacl-main.14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.738"},{"key":"ref16","article-title":"Distributed representations of words and phrases and their compositionality","author":"mikolov","year":"2013","journal-title":"NIPS"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10987"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.356"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482363"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM51629.2021.00112"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9413384"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00101"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053071"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.205"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053105"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347038"},{"key":"ref9","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2019"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.154"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP.2016.7738886"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482056"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412226"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.207"},{"key":"ref23","article-title":"Modelling session activity with neural embedding","author":"barkan","year":"2016","journal-title":"RecSys Posters"},{"key":"ref25","article-title":"A primer on contrastive pretraining in language processing: Methods, lessons learned and perspectives","author":"rethmeier","year":"2021"}],"event":{"name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Singapore, Singapore","start":{"date-parts":[[2022,5,23]]},"end":{"date-parts":[[2022,5,27]]}},"container-title":["ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9745891\/9746004\/09746018.pdf?arnumber=9746018","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T20:10:31Z","timestamp":1661199031000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9746018\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,23]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/icassp43922.2022.9746018","relation":{},"subject":[],"published":{"date-parts":[[2022,5,23]]}}}