{"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/transformers-meet-relational-databases","title":"Transformers Meet Relational Databases","arxiv_id":"2412.05218","date":"2024-12-06","proceeding":null,"authors":["Jakub Peleška","Gustav Šír"],"abstract":"Transformer models have continuously expanded into all machine learning domains convertible to the underlying sequence-to-sequence representation, including tabular data. However, while ubiquitous, this representation restricts their extension to the more general case of relational databases. In this paper, we introduce a modular neural message-passing scheme that closely adheres to the formal relational model, enabling direct end-to-end learning of tabular Transformers from database storage systems. We address the challenges of appropriate learning data representation and loading, which are critical in the database setting, and compare our approach against a number of representative models from various related fields across a significantly wide range of datasets. Our results demonstrate a superior performance of this newly proposed class of neural architectures.","url_abs":"https://arxiv.org/abs/2412.05218v1","url_pdf":"https://arxiv.org/pdf/2412.05218v1.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":"transformers-meet-relational-databases","repo_url":"https://github.com/jakubpeleska/deep-db-learning","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2412.05218","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.05218"}},"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/jakubpeleska/deep-db-learning","reach":{"status":"ok"}}],"summary":{"unverified":5},"by_repo_kind":{"official":{"samples":5,"ran":0,"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":5,"samples":[{"code_sha256_prefix":"dc35182231383243","entry":"get_fact_name","repo":"jakubpeleska/deep-db-learning","repo_kind":"official","path":"experiments/srlboost.py","file_url":"https://github.com/jakubpeleska/deep-db-learning/blob/HEAD/experiments/srlboost.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":"dc35182231383243"}},{"code_sha256_prefix":"6b2ab6b971eb16e8","entry":"get_string_mapper","repo":"jakubpeleska/deep-db-learning","repo_kind":"official","path":"db_transformer/db/distinct_cnt_retrieval.py","file_url":"https://github.com/jakubpeleska/deep-db-learning/blob/HEAD/db_transformer/db/distinct_cnt_retrieval.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":"6b2ab6b971eb16e8"}},{"code_sha256_prefix":"923bfc66288ab0dc","entry":"get_table_len","repo":"jakubpeleska/deep-db-learning","repo_kind":"official","path":"db_transformer/helpers/database.py","file_url":"https://github.com/jakubpeleska/deep-db-learning/blob/HEAD/db_transformer/helpers/database.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":"923bfc66288ab0dc"}},{"code_sha256_prefix":"287d3f45bddeb860","entry":"get_tune_config","repo":"jakubpeleska/deep-db-learning","repo_kind":"official","path":"experiments/blueprint_mlflow.py","file_url":"https://github.com/jakubpeleska/deep-db-learning/blob/HEAD/experiments/blueprint_mlflow.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":"287d3f45bddeb860"}},{"code_sha256_prefix":"995626bcd539b7c4","entry":"wrap_progress","repo":"jakubpeleska/deep-db-learning","repo_kind":"official","path":"db_transformer/helpers/progress.py","file_url":"https://github.com/jakubpeleska/deep-db-learning/blob/HEAD/db_transformer/helpers/progress.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":"995626bcd539b7c4"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}