{"url":"/method/esacl","slug":"esacl","name":"ESACL","full_name":"Enhanced Seq2Seq Autoencoder via Contrastive Learning","full_name_withheld":false,"description_markdown":"**ESACL**, or **Enhanced Seq2Seq Autoencoder via Contrastive Learning**, is a denoising sequence-to-sequence (seq2seq) autoencoder via contrastive learning for abstractive text summarization. The model adopts a standard [Transformer](https://paperswithcode.com/method/transformer)-based architecture with a multilayer bi-directional encoder and an autoregressive decoder. To enhance its denoising ability, self-supervised contrastive learning is incorporated along with various sentence-level document augmentation.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/2108.11992v1","title":"Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization","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":"Transformers","url":"/methods/category/transformers","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":null,"papers_newest_first":[{"paper":null,"title":"EsaCL: Efficient Continual Learning of Sparse Models","date":"2024-01-11","arxiv_id":"2401.05667","n_code_links":0,"syntology":null},{"paper":"/paper/enhanced-seq2seq-autoencoder-via-contrastive","title":"Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization","date":"2021-08-26","arxiv_id":"2108.11992","n_code_links":2,"syntology":null}],"papers_shown":2,"tasks":[{"task":"/task/abstractive-text-summarization","name":"Abstractive Text Summarization","papers":1},{"task":"/task/continual-learning","name":"Continual Learning","papers":1},{"task":"/task/contrastive-learning","name":"Contrastive Learning","papers":1},{"task":"/task/decoder","name":"Decoder","papers":1},{"task":"/task/denoising","name":"Denoising","papers":1},{"task":"/task/sentence","name":"Sentence","papers":1},{"task":"/task/text-summarization","name":"Text Summarization","papers":1}],"tasks_shown":7,"n_tasks":7,"usage_by_year":[{"year":"2021","papers":1},{"year":"2024","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/esacl"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}