{"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/vote-n-rank-revision-of-benchmarking-with","title":"Vote'n'Rank: Revision of Benchmarking with Social Choice Theory","arxiv_id":"2210.05769","date":"2022-10-11","proceeding":null,"authors":["Mark Rofin","Vladislav Mikhailov","Mikhail Florinskiy","Andrey Kravchenko","Elena Tutubalina","Tatiana Shavrina","Daniel Karabekyan","Ekaterina Artemova"],"abstract":"The development of state-of-the-art systems in different applied areas of machine learning (ML) is driven by benchmarks, which have shaped the paradigm of evaluating generalisation capabilities from multiple perspectives. Although the paradigm is shifting towards more fine-grained evaluation across diverse tasks, the delicate question of how to aggregate the performances has received particular interest in the community. In general, benchmarks follow the unspoken utilitarian principles, where the systems are ranked based on their mean average score over task-specific metrics. Such aggregation procedure has been viewed as a sub-optimal evaluation protocol, which may have created the illusion of progress. This paper proposes Vote'n'Rank, a framework for ranking systems in multi-task benchmarks under the principles of the social choice theory. We demonstrate that our approach can be efficiently utilised to draw new insights on benchmarking in several ML sub-fields and identify the best-performing systems in research and development case studies. The Vote'n'Rank's procedures are more robust than the mean average while being able to handle missing performance scores and determine conditions under which the system becomes the winner.","url_abs":"https://arxiv.org/abs/2210.05769v3","url_pdf":"https://arxiv.org/pdf/2210.05769v3.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":"vote-n-rank-revision-of-benchmarking-with","repo_url":"https://github.com/pragmaticslab/vote_and_rank","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"},{"task_slug":"result-aggregation","task_name":"Result aggregation"},{"task_slug":"skills-evaluation","task_name":"Skills Evaluation"}],"methods":[{"method_slug":"albert","method_name":"ALBERT"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"attention-dropout","method_name":"Attention Dropout"},{"method_slug":"bert","method_name":"BERT"},{"method_slug":"deberta","method_name":"DeBERTa"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"ernie","method_name":"ERNIE"},{"method_slug":"lamb","method_name":"LAMB"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"linear-warmup-with-linear-decay","method_name":"Linear Warmup With Linear Decay"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"weight-decay","method_name":"Weight Decay"},{"method_slug":"wordpiece","method_name":"WordPiece"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2210.05769","atlas_url":"https://app.syntology.ai/?focus=2210.05769","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2210.05769"}},"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/pragmaticslab/vote_and_rank","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran":6,"unverified":11},"by_repo_kind":{"official":{"samples":17,"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":0,"samples":[{"code_sha256_prefix":"24983cbbf10c380a","entry":"get_res_df","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/stability_exp.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/stability_exp.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"24983cbbf10c380a"}},{"code_sha256_prefix":"2753ffd283ace2c7","entry":"mean_ranking","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/leaderboard/_rules.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/leaderboard/_rules.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"2753ffd283ace2c7"}},{"code_sha256_prefix":"61ecad216e42085c","entry":"naive_masking_score","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/fairness_computation.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/fairness_computation.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"61ecad216e42085c"}},{"code_sha256_prefix":"335d437c607e19d1","entry":"naive_t5_score","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/fairness_computation.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/fairness_computation.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"335d437c607e19d1"}},{"code_sha256_prefix":"40e3b0bc93d87e29","entry":"preprocess_value","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/data_processing.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/data_processing.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"40e3b0bc93d87e29"}},{"code_sha256_prefix":"708a0312fba2e239","entry":"ranking2top","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/utils.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/utils.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"708a0312fba2e239"}},{"code_sha256_prefix":"62d6f8c97a21042f","entry":"agreement_rate","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/utils.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/utils.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":"62d6f8c97a21042f"}},{"code_sha256_prefix":"63a3462e0df18dbf","entry":"compute_iia","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/iia_exp.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/iia_exp.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":"63a3462e0df18dbf"}},{"code_sha256_prefix":"f391b7410d101195","entry":"compute_iia_for_fixed_models","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/iia_exp.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/iia_exp.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":"f391b7410d101195"}},{"code_sha256_prefix":"99837b3c6b7db771","entry":"fine_sorted_ranking","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/iia_exp.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/iia_exp.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":"99837b3c6b7db771"}},{"code_sha256_prefix":"c7b9ab94d004f31d","entry":"kendall_tau","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/utils.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/utils.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":"c7b9ab94d004f31d"}},{"code_sha256_prefix":"0b38e82dfe604c4a","entry":"mean_election","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/leaderboard/_rules.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/leaderboard/_rules.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":"0b38e82dfe604c4a"}},{"code_sha256_prefix":"fb36e5dc20e0a615","entry":"naive_gpt2_score","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/fairness_computation.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/fairness_computation.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":"fb36e5dc20e0a615"}},{"code_sha256_prefix":"259e4bac30e16d32","entry":"plurality_ranking","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/leaderboard/_rules.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/leaderboard/_rules.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":"259e4bac30e16d32"}},{"code_sha256_prefix":"ad5284fde4881978","entry":"preprocess_glue","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/data_processing.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/data_processing.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":"ad5284fde4881978"}},{"code_sha256_prefix":"dbcd5b79074ddddd","entry":"preprocess_sglue","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/data_processing.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/data_processing.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":"dbcd5b79074ddddd"}},{"code_sha256_prefix":"a6b079a0864a73e8","entry":"spearman_exp","repo":"pragmaticslab/vote_and_rank","repo_kind":"official","path":"votenrank/stability_exp.py","file_url":"https://github.com/pragmaticslab/vote_and_rank/blob/HEAD/votenrank/stability_exp.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":"a6b079a0864a73e8"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}