{"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/multi-group-proportional-representation","title":"Multi-Group Proportional Representation in Retrieval","arxiv_id":"2407.08571","date":"2024-07-11","proceeding":null,"authors":["Alex Oesterling","Claudio Mayrink Verdun","Carol Xuan Long","Alexander Glynn","Lucas Monteiro Paes","Sajani Vithana","Martina Cardone","Flavio P. Calmon"],"abstract":"Image search and retrieval tasks can perpetuate harmful stereotypes, erase cultural identities, and amplify social disparities. Current approaches to mitigate these representational harms balance the number of retrieved items across population groups defined by a small number of (often binary) attributes. However, most existing methods overlook intersectional groups determined by combinations of group attributes, such as gender, race, and ethnicity. We introduce Multi-Group Proportional Representation (MPR), a novel metric that measures representation across intersectional groups. We develop practical methods for estimating MPR, provide theoretical guarantees, and propose optimization algorithms to ensure MPR in retrieval. We demonstrate that existing methods optimizing for equal and proportional representation metrics may fail to promote MPR. Crucially, our work shows that optimizing MPR yields more proportional representation across multiple intersectional groups specified by a rich function class, often with minimal compromise in retrieval accuracy.","url_abs":"https://arxiv.org/abs/2407.08571v2","url_pdf":"https://arxiv.org/pdf/2407.08571v2.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":"multi-group-proportional-representation","repo_url":"https://github.com/alex-oesterling/multigroup-proportional-representation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"image-retrieval","task_name":"Image Retrieval"},{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2407.08571","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.08571"}},"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/alex-oesterling/multigroup-proportional-representation","reach":null}],"summary":{"ran_violates":1,"ran_fixture":2,"ran_draft_wrong":2},"by_repo_kind":{"official":{"samples":4,"ran":4,"repositories":1},"community":{"samples":1,"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":0,"samples":[{"code_sha256_prefix":"beaea7ef32f3d733","entry":"argmax_probe_labels","repo":"alex-oesterling/multigroup-proportional-representation","repo_kind":"official","path":"experiments/benchmark_retrieval.py","file_url":"https://github.com/alex-oesterling/multigroup-proportional-representation/blob/HEAD/experiments/benchmark_retrieval.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"beaea7ef32f3d733"}},{"code_sha256_prefix":"6d935dda756f725c","entry":"get_argsup","repo":"alex-oesterling/multigroup-proportional-representation","repo_kind":"official","path":"mpr/mpr.py","file_url":"https://github.com/alex-oesterling/multigroup-proportional-representation/blob/HEAD/mpr/mpr.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"6d935dda756f725c"}},{"code_sha256_prefix":"7f4ffc901786396d","entry":"get_top_embeddings_labels_ids","repo":"alex-oesterling/multigroup-proportional-representation","repo_kind":"official","path":"experiments/benchmark_retrieval.py","file_url":"https://github.com/alex-oesterling/multigroup-proportional-representation/blob/HEAD/experiments/benchmark_retrieval.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"7f4ffc901786396d"}},{"code_sha256_prefix":"21244d91823a0516","entry":"mpr","repo":"alex-oesterling/multigroup-proportional-representation","repo_kind":"official","path":"mpr/mpr.py","file_url":"https://github.com/alex-oesterling/multigroup-proportional-representation/blob/HEAD/mpr/mpr.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"21244d91823a0516"}},{"code_sha256_prefix":"f0c7bac63b048953","entry":"pre_handel","repo":"RunlongYu/BPR_MPR","repo_kind":"community","path":"BPR.py","file_url":"https://github.com/RunlongYu/BPR_MPR/blob/HEAD/BPR.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"f0c7bac63b048953"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}