{"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/sopa-bridging-cnns-rnns-and-weighted-finite","title":"SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines","arxiv_id":"1805.06061","date":"2018-05-15","proceeding":null,"authors":["Roy Schwartz","Sam Thomson","Noah A. Smith"],"abstract":"Recurrent and convolutional neural networks comprise two distinct families of\nmodels that have proven to be useful for encoding natural language utterances.\nIn this paper we present SoPa, a new model that aims to bridge these two\napproaches. SoPa combines neural representation learning with weighted\nfinite-state automata (WFSAs) to learn a soft version of traditional surface\npatterns. We show that SoPa is an extension of a one-layer CNN, and that such\nCNNs are equivalent to a restricted version of SoPa, and accordingly, to a\nrestricted form of WFSA. Empirically, on three text classification tasks, SoPa\nis comparable or better than both a BiLSTM (RNN) baseline and a CNN baseline,\nand is particularly useful in small data settings.","url_abs":"http://arxiv.org/abs/1805.06061v1","url_pdf":"http://arxiv.org/pdf/1805.06061v1.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":"sopa-bridging-cnns-rnns-and-weighted-finite","repo_url":"https://github.com/Noahs-ARK/soft_patterns","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"sopa-bridging-cnns-rnns-and-weighted-finite","repo_url":"https://github.com/atreyasha/spp-explainability","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"explainable-artificial-intelligence","task_name":"Explainable artificial intelligence"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"text-classification","task_name":"Text Classification"},{"task_slug":"text-classification-1","task_name":"text-classification"}],"methods":[{"method_slug":"bilstm","method_name":"BiLSTM"},{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1805.06061","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.06061"}},"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/atreyasha/spp-explainability","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Noahs-ARK/soft_patterns","reach":null}],"summary":{"ran_honours":3,"ran_draft_wrong":1,"unverified":1},"by_repo_kind":{"official":{"samples":2,"ran":2,"repositories":1},"listed":{"samples":3,"ran":2,"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":"af68a5b723fbd3c4","entry":"argmax","repo":"Noahs-ARK/soft_patterns","repo_kind":"official","path":"soft_patterns.py","file_url":"https://github.com/Noahs-ARK/soft_patterns/blob/HEAD/soft_patterns.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"af68a5b723fbd3c4"}},{"code_sha256_prefix":"abd57b2449dafbbe","entry":"fixed_var","repo":"Noahs-ARK/soft_patterns","repo_kind":"official","path":"soft_patterns.py","file_url":"https://github.com/Noahs-ARK/soft_patterns/blob/HEAD/soft_patterns.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"abd57b2449dafbbe"}},{"code_sha256_prefix":"fd442d47115bb365","entry":"get_exit_code","repo":"atreyasha/spp-explainability","repo_kind":"listed","path":"src/train_spp.py","file_url":"https://github.com/atreyasha/spp-explainability/blob/HEAD/src/train_spp.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"fd442d47115bb365"}},{"code_sha256_prefix":"dbd9b242356cf5d3","entry":"parse_configs_to_args","repo":"atreyasha/spp-explainability","repo_kind":"listed","path":"src/train_spp.py","file_url":"https://github.com/atreyasha/spp-explainability/blob/HEAD/src/train_spp.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":"dbd9b242356cf5d3"}},{"code_sha256_prefix":"73d6976f03da9f2c","entry":"set_hardware","repo":"atreyasha/spp-explainability","repo_kind":"listed","path":"src/train_spp.py","file_url":"https://github.com/atreyasha/spp-explainability/blob/HEAD/src/train_spp.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"73d6976f03da9f2c"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}