{"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/learning-fair-representations-via-rate","title":"Learning Fair Representations via Rate-Distortion Maximization","arxiv_id":"2202.00035","date":"2022-01-31","proceeding":null,"authors":["Somnath Basu Roy Chowdhury","Snigdha Chaturvedi"],"abstract":"Text representations learned by machine learning models often encode undesirable demographic information of the user. Predictive models based on these representations can rely on such information, resulting in biased decisions. We present a novel debiasing technique, Fairness-aware Rate Maximization (FaRM), that removes protected information by making representations of instances belonging to the same protected attribute class uncorrelated, using the rate-distortion function. FaRM is able to debias representations with or without a target task at hand. FaRM can also be adapted to remove information about multiple protected attributes simultaneously. Empirical evaluations show that FaRM achieves state-of-the-art performance on several datasets, and learned representations leak significantly less protected attribute information against an attack by a non-linear probing network.","url_abs":"https://arxiv.org/abs/2202.00035v2","url_pdf":"https://arxiv.org/pdf/2202.00035v2.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":"learning-fair-representations-via-rate","repo_url":"https://github.com/brcsomnath/farm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"},{"task_slug":"fairness","task_name":"Fairness"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2202.00035","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.00035"}},"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/brcsomnath/farm","reach":null}],"summary":{"ran_honours":1,"ran_draft_wrong":5,"unverified":1},"by_repo_kind":{"official":{"samples":7,"ran":6,"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":7,"samples":[{"code_sha256_prefix":"e686ca185ffdaef5","entry":"encode","repo":"brcsomnath/farm","repo_kind":"official","path":"src/unconstrained/glove-embeddings.py","file_url":"https://github.com/brcsomnath/farm/blob/HEAD/src/unconstrained/glove-embeddings.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"e686ca185ffdaef5"}},{"code_sha256_prefix":"622d9b61220fef40","entry":"encode","repo":"brcsomnath/farm","repo_kind":"official","path":"src/constrained/constrained-single.py","file_url":"https://github.com/brcsomnath/farm/blob/HEAD/src/constrained/constrained-single.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":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"622d9b61220fef40"}},{"code_sha256_prefix":"38566e02a626bc34","entry":"form_dataset","repo":"brcsomnath/farm","repo_kind":"official","path":"src/unconstrained/glove-embeddings.py","file_url":"https://github.com/brcsomnath/farm/blob/HEAD/src/unconstrained/glove-embeddings.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":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"38566e02a626bc34"}},{"code_sha256_prefix":"fb09141828e509d0","entry":"get_dataset","repo":"brcsomnath/farm","repo_kind":"official","path":"src/constrained/constrained-single.py","file_url":"https://github.com/brcsomnath/farm/blob/HEAD/src/constrained/constrained-single.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":"fb09141828e509d0"}},{"code_sha256_prefix":"abef5bdd6d4d119a","entry":"label_to_membership","repo":"brcsomnath/farm","repo_kind":"official","path":"src/utils/loss.py","file_url":"https://github.com/brcsomnath/farm/blob/HEAD/src/utils/loss.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":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"abef5bdd6d4d119a"}},{"code_sha256_prefix":"62dfecd92146a155","entry":"one_hot","repo":"brcsomnath/farm","repo_kind":"official","path":"src/utils/loss.py","file_url":"https://github.com/brcsomnath/farm/blob/HEAD/src/utils/loss.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"62dfecd92146a155"}},{"code_sha256_prefix":"5268ed92858a7c3a","entry":"generate_debiased_embeddings","repo":"brcsomnath/farm","repo_kind":"official","path":"src/unconstrained/glove-embeddings.py","file_url":"https://github.com/brcsomnath/farm/blob/HEAD/src/unconstrained/glove-embeddings.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":"5268ed92858a7c3a"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}