{"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/clip-dissect-automatic-description-of-neuron","title":"CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks","arxiv_id":"2204.10965","date":"2022-04-23","proceeding":null,"authors":["Tuomas Oikarinen","Tsui-Wei Weng"],"abstract":"In this paper, we propose CLIP-Dissect, a new technique to automatically describe the function of individual hidden neurons inside vision networks. CLIP-Dissect leverages recent advances in multimodal vision/language models to label internal neurons with open-ended concepts without the need for any labeled data or human examples. We show that CLIP-Dissect provides more accurate descriptions than existing methods for last layer neurons where the ground-truth is available as well as qualitatively good descriptions for hidden layer neurons. In addition, our method is very flexible: it is model agnostic, can easily handle new concepts and can be extended to take advantage of better multimodal models in the future. Finally CLIP-Dissect is computationally efficient and can label all neurons from five layers of ResNet-50 in just 4 minutes, which is more than 10 times faster than existing methods. Our code is available at https://github.com/Trustworthy-ML-Lab/CLIP-dissect. Finally, crowdsourced user study results are available at Appendix B to further support the effectiveness of our method.","url_abs":"https://arxiv.org/abs/2204.10965v5","url_pdf":"https://arxiv.org/pdf/2204.10965v5.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":"clip-dissect-automatic-description-of-neuron","repo_url":"https://github.com/trustworthy-ml-lab/clip-dissect","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"clip-dissect-automatic-description-of-neuron","repo_url":"https://github.com/lkopf/cosy","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"clip-dissect-automatic-description-of-neuron","repo_url":"https://github.com/neuroexplicit-saar/discover-then-name","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"jax","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"clip-dissect-automatic-description-of-neuron","repo_url":"https://github.com/teresa-sc/concepts_in_vits","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2204.10965","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.10965"}},"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":"deterministic:regex_extraction","url":"https://github.com/Trustworthy-ML-Lab/CLIPdissect","reach":{"status":"gone","observed_at":"2026-09-17","how":"tree_404+repo_404"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/neuroexplicit-saar/discover-then-name","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/lkopf/cosy","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/trustworthy-ml-lab/clip-dissect","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/teresa-sc/concepts_in_vits","reach":null}],"summary":{"ran_draft_wrong":2,"ran":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"repositories":1},"listed":{"samples":2,"ran":2,"repositories":2}},"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":3,"samples":[{"code_sha256_prefix":"cc642412d4347cce","entry":"cos_similarity","repo":"teresa-sc/concepts_in_vits","repo_kind":"listed","path":"similarity.py","file_url":"https://github.com/teresa-sc/concepts_in_vits/blob/HEAD/similarity.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"cc642412d4347cce"}},{"code_sha256_prefix":"0ad66fe23e6598ce","entry":"get_activations","repo":"lkopf/cosy","repo_kind":"listed","path":"src/utils.py","file_url":"https://github.com/lkopf/cosy/blob/HEAD/src/utils.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"0ad66fe23e6598ce"}},{"code_sha256_prefix":"01ae9d2d9c845331","entry":"soft_wpmi","repo":"trustworthy-ml-lab/clip-dissect","repo_kind":"official","path":"similarity.py","file_url":"https://github.com/trustworthy-ml-lab/clip-dissect/blob/HEAD/similarity.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"01ae9d2d9c845331"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}