{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/coreference-resolution-without-span","title":"Coreference Resolution without Span Representations","arxiv_id":"2101.00434","date":"2021-01-02","proceeding":"ACL 2021 5","authors":["Yuval Kirstain","Ori Ram","Omer Levy"],"abstract":"The introduction of pretrained language models has reduced many complex task-specific NLP models to simple lightweight layers. An exception to this trend is coreference resolution, where a sophisticated task-specific model is appended to a pretrained transformer encoder. While highly effective, the model has a very large memory footprint -- primarily due to dynamically-constructed span and span-pair representations -- which hinders the processing of complete documents and the ability to train on multiple instances in a single batch. We introduce a lightweight end-to-end coreference model that removes the dependency on span representations, handcrafted features, and heuristics. Our model performs competitively with the current standard model, while being simpler and more efficient.","url_abs":"https://arxiv.org/abs/2101.00434v2","url_pdf":"https://arxiv.org/pdf/2101.00434v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"coreference-resolution-without-span","repo_url":"https://github.com/yuvalkirstain/s2e-coref","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"coreference-resolution","task_name":"Coreference Resolution"},{"task_slug":"coreference-resolution-1","task_name":"coreference-resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/coreference-resolution-on-conll-2012","task":"Coreference Resolution","dataset":"CoNLL 2012","model":"s2e + Longformer-Large","rank_in_archive_order":6,"of":18,"metrics":{"Avg F1":"80.3"},"uses_additional_data":false},{"leaderboard":"/sota/coreference-resolution-on-conll-2012","task":"Coreference Resolution","dataset":"CoNLL 2012","model":"c2f + SpanBERT-Large","rank_in_archive_order":8,"of":18,"metrics":{"Avg F1":"80.2"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2101.00434","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}