{"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/macro-average-rare-types-are-important-too","title":"Macro-Average: Rare Types Are Important Too","arxiv_id":"2104.05700","date":"2021-04-12","proceeding":"NAACL 2021 4","authors":["Thamme Gowda","Weiqiu You","Constantine Lignos","Jonathan May"],"abstract":"While traditional corpus-level evaluation metrics for machine translation (MT) correlate well with fluency, they struggle to reflect adequacy. Model-based MT metrics trained on segment-level human judgments have emerged as an attractive replacement due to strong correlation results. These models, however, require potentially expensive re-training for new domains and languages. Furthermore, their decisions are inherently non-transparent and appear to reflect unwelcome biases. We explore the simple type-based classifier metric, MacroF1, and study its applicability to MT evaluation. We find that MacroF1 is competitive on direct assessment, and outperforms others in indicating downstream cross-lingual information retrieval task performance. Further, we show that MacroF1 can be used to effectively compare supervised and unsupervised neural machine translation, and reveal significant qualitative differences in the methods' outputs.","url_abs":"https://arxiv.org/abs/2104.05700v1","url_pdf":"https://arxiv.org/pdf/2104.05700v1.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":"macro-average-rare-types-are-important-too","repo_url":"https://github.com/thammegowda/007-mt-eval-macro","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"cross-lingual-information-retrieval","task_name":"Cross-Lingual Information Retrieval"},{"task_slug":"information-retrieval","task_name":"Information Retrieval"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"retrieval","task_name":"Retrieval"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2104.05700","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.05700"}},"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/thammegowda/007-mt-eval-macro","reach":{"status":"ok"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/isi-nlp/sacrebleu","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran":1,"unverified":5},"by_repo_kind":{"found_in_text":{"samples":6,"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":"09bfbf9dc612b494","entry":"smart_open","repo":"isi-nlp/sacrebleu","repo_kind":"found_in_text","path":"sacrebleu/utils.py","file_url":"https://github.com/isi-nlp/sacrebleu/blob/HEAD/sacrebleu/utils.py","link_basis":"plan_row","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":"09bfbf9dc612b494"}},{"code_sha256_prefix":"5fba04efdb26053b","entry":"my_log","repo":"isi-nlp/sacrebleu","repo_kind":"found_in_text","path":"sacrebleu/utils.py","file_url":"https://github.com/isi-nlp/sacrebleu/blob/HEAD/sacrebleu/utils.py","link_basis":"first_harvest_node","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":"5fba04efdb26053b"}},{"code_sha256_prefix":"292d817868131fde","entry":"process_to_text","repo":"isi-nlp/sacrebleu","repo_kind":"found_in_text","path":"sacrebleu/utils.py","file_url":"https://github.com/isi-nlp/sacrebleu/blob/HEAD/sacrebleu/utils.py","link_basis":"first_harvest_node","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":"292d817868131fde"}},{"code_sha256_prefix":"773dd52da7e1cddf","entry":"safe_log","repo":"isi-nlp/sacrebleu","repo_kind":"found_in_text","path":"sacrebleu/metrics/base.py","file_url":"https://github.com/isi-nlp/sacrebleu/blob/HEAD/sacrebleu/metrics/base.py","link_basis":"first_harvest_node","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":"773dd52da7e1cddf"}},{"code_sha256_prefix":"56a33736d5ba06ae","entry":"trace_to_alignment","repo":"isi-nlp/sacrebleu","repo_kind":"found_in_text","path":"sacrebleu/metrics/ter.py","file_url":"https://github.com/isi-nlp/sacrebleu/blob/HEAD/sacrebleu/metrics/ter.py","link_basis":"first_harvest_node","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":"56a33736d5ba06ae"}},{"code_sha256_prefix":"ea5ec73260fe384b","entry":"translation_edit_rate","repo":"isi-nlp/sacrebleu","repo_kind":"found_in_text","path":"sacrebleu/metrics/ter.py","file_url":"https://github.com/isi-nlp/sacrebleu/blob/HEAD/sacrebleu/metrics/ter.py","link_basis":"first_harvest_node","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":"ea5ec73260fe384b"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}