{"url":"/method/big-little-module","slug":"big-little-module","name":"Big-Little Module","full_name":"Big-Little Module","full_name_withheld":false,"description_markdown":"**Big-Little Modules** are blocks for image models that have two branches: each of which represents a separate block from a deep model and a less deep counterpart. They were proposed as part of the [BigLittle-Net](https://paperswithcode.com/method/big-little-net) architecture. The two branches are fused with a linear combination and unit weights. These two branches are known as Big-Branch (more layers and channels at low resolutions) and Little-Branch (fewer layers and channels at high resolution).","description_state":"present","introduced_year":null,"introduced_by":{"title":"Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition","paper":"/paper/big-little-net-an-efficient-multi-scale","first_author":"Chun-Fu Chen","n_authors":5,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/big-little-net-an-efficient-multi-scale"},"source":{"url":"https://arxiv.org/abs/1807.03848v3","title":"Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/IBM/BigLittleNet/blob/dff465428df4e921fdb73ac5cd4510c20b303d95/models/blresnet.py#L63","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Image Model Blocks","url":"/methods/category/image-model-blocks","pwc_aliases":[]},{"area":"General","area_id":"general","collection":"Skip Connection Blocks","url":"/methods/category/skip-connection-blocks","pwc_aliases":[]}],"n_papers_tagged":4,"archive_num_papers":4,"papers_newest_first":[{"paper":null,"title":"Large Scale Neural Architecture Search with Polyharmonic Splines","date":"2020-11-20","arxiv_id":"2011.10608","n_code_links":0,"syntology":null},{"paper":"/paper/wavegrad-estimating-gradients-for-waveform","title":"WaveGrad: Estimating Gradients for Waveform Generation","date":"2020-09-02","arxiv_id":"2009.00713","n_code_links":7,"syntology":{"ran":1,"of":3,"unverified":2,"pointer_only":1}},{"paper":"/paper/compounding-the-performance-improvements-of","title":"Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network","date":"2020-01-17","arxiv_id":"2001.06268","n_code_links":1,"syntology":{"ran":1,"of":11,"unverified":10,"pointer_only":0}},{"paper":"/paper/big-little-net-an-efficient-multi-scale","title":"Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition","date":"2018-07-10","arxiv_id":"1807.03848","n_code_links":3,"syntology":null}],"papers_shown":4,"tasks":[{"task":"/task/image-classification","name":"Image Classification","papers":2},{"task":"/task/image-classification","name":"image-classification","papers":2},{"task":"/task/fine-grained-image-classification","name":"Fine-Grained Image Classification","papers":1},{"task":"/task/fine-grained-visual-recognition","name":"Fine-Grained Visual Recognition","papers":1},{"task":"/task/classification","name":"General Classification","papers":1},{"task":"/task/image-retrieval","name":"Image Retrieval","papers":1},{"task":"/task/architecture-search","name":"Neural Architecture Search","papers":1},{"task":"/task/object","name":"Object","papers":1},{"task":"/task/object-recognition","name":"Object Recognition","papers":1},{"task":"/task/retrieval","name":"Retrieval","papers":1},{"task":"/task/speech-recognition","name":"Speech Recognition","papers":1},{"task":"/task/speech-synthesis","name":"Speech Synthesis","papers":1},{"task":"/task/text-to-speech-synthesis","name":"Text-To-Speech Synthesis","papers":1},{"task":"/task/transfer-learning","name":"Transfer Learning","papers":1},{"task":"/task/speech-recognition-1","name":"speech-recognition","papers":1}],"tasks_shown":15,"n_tasks":15,"usage_by_year":[{"year":"2018","papers":1},{"year":"2020","papers":3}],"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/big-little-module"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}