{"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/disco-remedy-self-supervised-learning-on","title":"DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning","arxiv_id":"2104.09124","date":"2021-04-19","proceeding":null,"authors":["Yuting Gao","Jia-Xin Zhuang","Shaohui Lin","Hao Cheng","Xing Sun","Ke Li","Chunhua Shen"],"abstract":"While self-supervised representation learning (SSL) has received widespread attention from the community, recent research argue that its performance will suffer a cliff fall when the model size decreases. The current method mainly relies on contrastive learning to train the network and in this work, we propose a simple yet effective Distilled Contrastive Learning (DisCo) to ease the issue by a large margin. Specifically, we find the final embedding obtained by the mainstream SSL methods contains the most fruitful information, and propose to distill the final embedding to maximally transmit a teacher's knowledge to a lightweight model by constraining the last embedding of the student to be consistent with that of the teacher. In addition, in the experiment, we find that there exists a phenomenon termed Distilling BottleNeck and present to enlarge the embedding dimension to alleviate this problem. Our method does not introduce any extra parameter to lightweight models during deployment. Experimental results demonstrate that our method achieves the state-of-the-art on all lightweight models. Particularly, when ResNet-101/ResNet-50 is used as teacher to teach EfficientNet-B0, the linear result of EfficientNet-B0 on ImageNet is very close to ResNet-101/ResNet-50, but the number of parameters of EfficientNet-B0 is only 9.4\\%/16.3\\% of ResNet-101/ResNet-50. Code is available at https://github. com/Yuting-Gao/DisCo-pytorch.","url_abs":"https://arxiv.org/abs/2104.09124v7","url_pdf":"https://arxiv.org/pdf/2104.09124v7.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":"disco-remedy-self-supervised-learning-on","repo_url":"https://github.com/Yuting-Gao/DisCo-pytorch","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"disco-remedy-self-supervised-learning-on","repo_url":"https://github.com/lyqcom/DisCo","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"contrastive-learning","task_name":"Contrastive Learning"},{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"self-supervised-learning","task_name":"Self-Supervised Learning"}],"methods":[{"method_slug":"contrastive-learning","method_name":"Contrastive Learning"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2104.09124","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.09124"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Yuting-Gao/DisCo-pytorch","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/lyqcom/DisCo","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"unverified":4},"by_repo_kind":{"listed":{"samples":4,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"8d7b4240eee03907","entry":"TwoCropsTransform","repo":"lyqcom/DisCo","repo_kind":"listed","path":"DisCo/dataset_ms.py","file_url":"https://github.com/lyqcom/DisCo/blob/HEAD/DisCo/dataset_ms.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"8d7b4240eee03907"}},{"code_sha256_prefix":"82c48515ddda4614","entry":"calculate_gain","repo":"lyqcom/DisCo","repo_kind":"listed","path":"DisCo/ResNet_ms.py","file_url":"https://github.com/lyqcom/DisCo/blob/HEAD/DisCo/ResNet_ms.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"82c48515ddda4614"}},{"code_sha256_prefix":"18c07acccd255281","entry":"get_last_checkpoint","repo":"lyqcom/DisCo","repo_kind":"listed","path":"MoCo/train_ms.py","file_url":"https://github.com/lyqcom/DisCo/blob/HEAD/MoCo/train_ms.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"18c07acccd255281"}},{"code_sha256_prefix":"f0a6216664197738","entry":"kaiming_normal","repo":"lyqcom/DisCo","repo_kind":"listed","path":"DisCo/ResNet_ms.py","file_url":"https://github.com/lyqcom/DisCo/blob/HEAD/DisCo/ResNet_ms.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"f0a6216664197738"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}