{"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/dataset-distillation-via-vision-language","title":"Dataset Distillation via Vision-Language Category Prototype","arxiv_id":"2506.23580","date":"2025-06-30","proceeding":null,"authors":["Yawen Zou","Guang Li","Duo Su","Zi Wang","Jun Yu","Chao Zhang"],"abstract":"Dataset distillation (DD) condenses large datasets into compact yet informative substitutes, preserving performance comparable to the original dataset while reducing storage, transmission costs, and computational consumption. However, previous DD methods mainly focus on distilling information from images, often overlooking the semantic information inherent in the data. The disregard for context hinders the model's generalization ability, particularly in tasks involving complex datasets, which may result in illogical outputs or the omission of critical objects. In this study, we integrate vision-language methods into DD by introducing text prototypes to distill language information and collaboratively synthesize data with image prototypes, thereby enhancing dataset distillation performance. Notably, the text prototypes utilized in this study are derived from descriptive text information generated by an open-source large language model. This framework demonstrates broad applicability across datasets without pre-existing text descriptions, expanding the potential of dataset distillation beyond traditional image-based approaches. Compared to other methods, the proposed approach generates logically coherent images containing target objects, achieving state-of-the-art validation performance and demonstrating robust generalization. Source code and generated data are available in https://github.com/zou-yawen/Dataset-Distillation-via-Vision-Language-Category-Prototype/","url_abs":"https://arxiv.org/abs/2506.23580v1","url_pdf":"https://arxiv.org/pdf/2506.23580v1.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":"dataset-distillation-via-vision-language","repo_url":"https://github.com/Guang000/Awesome-Dataset-Distillation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"dataset-distillation-via-vision-language","repo_url":"https://github.com/zou-yawen/dataset-distillation-via-vision-language-category-prototype","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"dataset-distillation","task_name":"Dataset Distillation"},{"task_slug":"descriptive","task_name":"Descriptive"},{"task_slug":"large-language-model","task_name":"Large Language Model"}],"methods":[{"method_slug":"focus","method_name":"Focus"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2506.23580","atlas_url":"https://app.syntology.ai/?focus=2506.23580","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2506.23580"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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/Guang000/Awesome-Dataset-Distillation","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zou-yawen/dataset-distillation-via-vision-language-category-prototype","reach":null}],"summary":{"ran_draft_wrong":1,"unverified":1},"by_repo_kind":{"official":{"samples":2,"ran":1,"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":2,"samples":[{"code_sha256_prefix":"68efeb6c1584567b","entry":"find_max_word_sentence","repo":"zou-yawen/dataset-distillation-via-vision-language-category-prototype","repo_kind":"official","path":"03_distiilation/gen_prototype.py","file_url":"https://github.com/zou-yawen/dataset-distillation-via-vision-language-category-prototype/blob/HEAD/03_distiilation/gen_prototype.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"68efeb6c1584567b"}},{"code_sha256_prefix":"e6303bbf6527d26e","entry":"gen_prototype","repo":"zou-yawen/dataset-distillation-via-vision-language-category-prototype","repo_kind":"official","path":"03_distiilation/gen_prototype.py","file_url":"https://github.com/zou-yawen/dataset-distillation-via-vision-language-category-prototype/blob/HEAD/03_distiilation/gen_prototype.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"e6303bbf6527d26e"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}