{"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/colorless-green-recurrent-networks-dream","title":"Colorless green recurrent networks dream hierarchically","arxiv_id":"1803.11138","date":"2018-03-29","proceeding":"NAACL 2018 6","authors":["Kristina Gulordava","Piotr Bojanowski","Edouard Grave","Tal Linzen","Marco Baroni"],"abstract":"Recurrent neural networks (RNNs) have achieved impressive results in a\nvariety of linguistic processing tasks, suggesting that they can induce\nnon-trivial properties of language. We investigate here to what extent RNNs\nlearn to track abstract hierarchical syntactic structure. We test whether RNNs\ntrained with a generic language modeling objective in four languages (Italian,\nEnglish, Hebrew, Russian) can predict long-distance number agreement in various\nconstructions. We include in our evaluation nonsensical sentences where RNNs\ncannot rely on semantic or lexical cues (\"The colorless green ideas I ate with\nthe chair sleep furiously\"), and, for Italian, we compare model performance to\nhuman intuitions. Our language-model-trained RNNs make reliable predictions\nabout long-distance agreement, and do not lag much behind human performance. We\nthus bring support to the hypothesis that RNNs are not just shallow-pattern\nextractors, but they also acquire deeper grammatical competence.","url_abs":"http://arxiv.org/abs/1803.11138v1","url_pdf":"http://arxiv.org/pdf/1803.11138v1.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":"colorless-green-recurrent-networks-dream","repo_url":"https://github.com/facebookresearch/colorlessgreenRNNs","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"colorless-green-recurrent-networks-dream","repo_url":"https://github.com/sheng-fu/colorlessgreenRNNs","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1803.11138","atlas_url":"https://app.syntology.ai/?focus=1803.11138","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.11138"}},"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/sheng-fu/colorlessgreenRNNs","reach":{"status":"ok","spdx":"NOASSERTION"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/facebookresearch/colorlessgreenRNNs","reach":null}],"summary":{"ran_draft_wrong":1},"by_repo_kind":{"official":{"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":1,"samples":[{"code_sha256_prefix":"f10c159718f91bd8","entry":"query_KenLM","repo":"facebookresearch/colorlessgreenRNNs","repo_kind":"official","path":"src/syntactic_testsets/evaluate_utils.py","file_url":"https://github.com/facebookresearch/colorlessgreenRNNs/blob/HEAD/src/syntactic_testsets/evaluate_utils.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":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"f10c159718f91bd8"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}