{"url":"/method/hbmp","slug":"hbmp","name":"HBMP","full_name":"Hierarchical BiLSTM Max Pooling","full_name_withheld":false,"description_markdown":"HBMP is a hierarchy-like structure of [BiLSTM](https://paperswithcode.com/method/bilstm) layers with [max pooling](https://paperswithcode.com/method/max-pooling). All in all, this model improves the previous state of the art for SciTail and achieves strong results for the SNLI and MultiNLI.","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/1808.08762v2","title":"Sentence Embeddings in NLI with Iterative Refinement Encoders","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Sequential","area_id":"sequential","collection":"Sequence To Sequence Models","url":"/methods/category/sequence-to-sequence-models","pwc_aliases":[]}],"n_papers_tagged":3,"archive_num_papers":null,"papers_newest_first":[{"paper":"/paper/farstail-a-persian-natural-language-inference","title":"FarsTail: A Persian Natural Language Inference Dataset","date":"2020-09-18","arxiv_id":"2009.08820","n_code_links":1,"syntology":null},{"paper":"/paper/learning-hierarchical-behavior-and-motion","title":"Learning hierarchical behavior and motion planning for autonomous driving","date":"2020-05-08","arxiv_id":"2005.03863","n_code_links":1,"syntology":null},{"paper":"/paper/natural-language-inference-with-hierarchical","title":"Sentence Embeddings in NLI with Iterative Refinement Encoders","date":"2018-08-27","arxiv_id":"1808.08762","n_code_links":1,"syntology":null}],"papers_shown":3,"tasks":[{"task":"/task/natural-language-inference","name":"Natural Language Inference","papers":2},{"task":"/task/autonomous-driving","name":"Autonomous Driving","papers":1},{"task":"/task/decision-making","name":"Decision Making","papers":1},{"task":"/task/motion-planning","name":"Motion Planning","papers":1},{"task":"/task/multiple-choice","name":"Multiple-choice","papers":1},{"task":"/task/reinforcement-learning-1","name":"Reinforcement Learning (RL)","papers":1},{"task":"/task/sentence","name":"Sentence","papers":1},{"task":"/task/sentence-embedding","name":"Sentence Embedding","papers":1},{"task":"/task/sentence-embeddings","name":"Sentence Embeddings","papers":1},{"task":"/task/sentence-embedding-1","name":"Sentence-Embedding","papers":1},{"task":"/task/transfer-learning","name":"Transfer Learning","papers":1}],"tasks_shown":11,"n_tasks":11,"usage_by_year":[{"year":"2018","papers":1},{"year":"2020","papers":2}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/hbmp"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}