{"url":"/method/binarybert","slug":"binarybert","name":"BinaryBERT","full_name":"BinaryBERT","full_name_withheld":false,"description_markdown":"**BinaryBERT** is a [BERT](https://paperswithcode.com/method/bert)-variant that applies quantization in the form of weight binarization. Specifically, ternary weight splitting is proposed which initializes BinaryBERT by equivalently splitting from a half-sized ternary network. To obtain BinaryBERT, we first train a half-sized [ternary BERT](https://paperswithcode.com/method/ternarybert) model, and then apply a [ternary weight splitting](https://paperswithcode.com/method/ternary-weight-splitting) operator to obtain the latent full-precision and quantized weights as the initialization of the full-sized BinaryBERT. We then fine-tune BinaryBERT for further refinement.","description_state":"present","introduced_year":null,"introduced_by":{"title":"BinaryBERT: Pushing the Limit of BERT Quantization","paper":"/paper/binarybert-pushing-the-limit-of-bert","first_author":"Haoli Bai","n_authors":9,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/binarybert-pushing-the-limit-of-bert"},"source":{"url":"https://arxiv.org/abs/2012.15701v2","title":"BinaryBERT: Pushing the Limit of BERT Quantization","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Natural Language Processing","area_id":"natural-language-processing","collection":"Autoencoding Transformers","url":"/methods/category/autoencoding-transformers","pwc_aliases":[]},{"area":"Natural Language Processing","area_id":"natural-language-processing","collection":"Transformers","url":"/methods/category/transformers","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":1,"papers_newest_first":[{"paper":"/paper/binarybert-pushing-the-limit-of-bert","title":"BinaryBERT: Pushing the Limit of BERT Quantization","date":"2020-12-31","arxiv_id":"2012.15701","n_code_links":1,"syntology":{"ran":4,"of":6,"unverified":2,"pointer_only":6}}],"papers_shown":1,"tasks":[{"task":"/task/binarization","name":"Binarization","papers":1},{"task":"/task/model-compression","name":"Model Compression","papers":1},{"task":"/task/quantization","name":"Quantization","papers":1}],"tasks_shown":3,"n_tasks":3,"usage_by_year":[{"year":"2020","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/binarybert"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}