{"about":{"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.","site":"https://codewithpapers.app","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","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/click-through-rate-prediction/papers/ran/1","list_of":"/task/click-through-rate-prediction","task":"Click-Through Rate Prediction","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not run it on this task or check it against the task's benchmarks.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":1,"pages_in_order":1,"rows_per_page":100,"rows":[1,25],"of":25,"counts":{"archive_papers_tagged":391,"with_a_code_link":165,"where_syntology_ran_a_sample":25,"not_listed_spam_title":0,"listed":391,"listed_where_code_ran":25,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":25,"every_run_a_failure_of_syntologys_instrument":0,"listed_with_a_run_with_no_instrument_failure":25,"listed_every_run_a_failure_of_syntologys_instrument":0,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/click-through-rate-prediction/papers/ran/1","prev":null,"next":null,"papers":[{"url":"/paper/temporal-interest-network-for-click-through","slug":"temporal-interest-network-for-click-through","title":"Temporal Interest Network for User Response Prediction","date":"2023-08-15","arxiv_id":"2308.08487","repositories_listed":2,"syntology":{"n":7,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":7,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/temporal-interest-network-for-click-through#ran","syntology_url":"https://syntology.ai/paper/2308.08487","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.08487"}},"official":{"repos":["zhouxy1003/tin"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/map-a-model-agnostic-pretraining-framework","slug":"map-a-model-agnostic-pretraining-framework","title":"MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction","date":"2023-08-03","arxiv_id":"2308.01737","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/map-a-model-agnostic-pretraining-framework#ran","syntology_url":"https://syntology.ai/paper/2308.01737","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.01737"}},"official":{"repos":["chiangel/map-code"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/finalmlp-an-enhanced-two-stream-mlp-model-for-1","slug":"finalmlp-an-enhanced-two-stream-mlp-model-for-1","title":"FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction","date":"2023-04-03","arxiv_id":"2304.00902","repositories_listed":4,"syntology":{"n":16,"n_ran":13,"n_constructed":4,"n_ran_checked":8,"n_instrument":5,"n_unverified":3,"n_honours":1,"n_violates":1,"n_no_contract":6,"n_pointer_only":0,"phrase":"13 ran (of which 4 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 1 violated, 6 with no contract checked; 5 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/finalmlp-an-enhanced-two-stream-mlp-model-for-1#ran","syntology_url":"https://syntology.ai/paper/2304.00902","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.00902"}},"official":{"repos":["reczoo/RecZoo"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/optimizing-feature-set-for-click-through-rate","slug":"optimizing-feature-set-for-click-through-rate","title":"Optimizing Feature Set for Click-Through Rate Prediction","date":"2023-01-26","arxiv_id":"2301.10909","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/optimizing-feature-set-for-click-through-rate#ran","syntology_url":"https://syntology.ai/paper/2301.10909","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2301.10909"}},"official":{"repos":["fuyuanlyu/optfs"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/bars-towards-open-benchmarking-for","slug":"bars-towards-open-benchmarking-for","title":"BARS: Towards Open Benchmarking for Recommender Systems","date":"2022-05-19","arxiv_id":"2205.09626","repositories_listed":5,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/bars-towards-open-benchmarking-for#ran","syntology_url":"https://syntology.ai/paper/2205.09626","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.09626"}},"official":{"repos":["openbenchmark/BARS"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/enhancing-ctr-prediction-with-context-aware","slug":"enhancing-ctr-prediction-with-context-aware","title":"Enhancing CTR Prediction with Context-Aware Feature Representation Learning","date":"2022-04-19","arxiv_id":"2204.08758","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/enhancing-ctr-prediction-with-context-aware#ran","syntology_url":"https://syntology.ai/paper/2204.08758","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.08758"}},"official":{"repos":["frnetnetwork/frnet"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/memorize-factorize-or-be-naive-learning","slug":"memorize-factorize-or-be-naive-learning","title":"Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction","date":"2021-08-03","arxiv_id":"2108.01265","repositories_listed":1,"syntology":{"n":9,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/memorize-factorize-or-be-naive-learning#ran","syntology_url":"https://syntology.ai/paper/2108.01265","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.01265"}},"official":{"repos":["fuyuanlyu/OptInter"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/fuxictr-an-open-benchmark-for-click-through","slug":"fuxictr-an-open-benchmark-for-click-through","title":"BARS-CTR: Open Benchmarking for Click-Through Rate Prediction","date":"2020-09-12","arxiv_id":"2009.05794","repositories_listed":6,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/fuxictr-an-open-benchmark-for-click-through#ran","syntology_url":"https://syntology.ai/paper/2009.05794","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.05794"}},"official":{"repos":["reczoo/BARS"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/dcn-m-improved-deep-cross-network-for-feature","slug":"dcn-m-improved-deep-cross-network-for-feature","title":"DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems","date":"2020-08-19","arxiv_id":"2008.13535","repositories_listed":12,"syntology":{"n":14,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/dcn-m-improved-deep-cross-network-for-feature#ran","syntology_url":"https://syntology.ai/paper/2008.13535","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.13535"}},"official":{"repos":["tensorflow/recommenders"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/autofis-automatic-feature-interaction","slug":"autofis-automatic-feature-interaction","title":"AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction","date":"2020-03-25","arxiv_id":"2003.11235","repositories_listed":6,"syntology":{"n":24,"n_ran":22,"n_constructed":0,"n_ran_checked":21,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":21,"n_pointer_only":1,"phrase":"22 ran (of which 0 constructed an object rather than computing a result; 21 with no instrument failure: 0 honoured, 0 violated, 21 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/autofis-automatic-feature-interaction#ran","syntology_url":"https://syntology.ai/paper/2003.11235","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.11235"}},"official":{"repos":["zhuchenxv/AutoFIS"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/mixed-dimension-embeddings-with-application","slug":"mixed-dimension-embeddings-with-application","title":"Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems","date":"2019-09-25","arxiv_id":"1909.11810","repositories_listed":6,"syntology":{"n":26,"n_ran":21,"n_constructed":0,"n_ran_checked":20,"n_instrument":1,"n_unverified":5,"n_honours":1,"n_violates":0,"n_no_contract":19,"n_pointer_only":26,"phrase":"21 ran (of which 0 constructed an object rather than computing a result; 20 with no instrument failure: 1 honoured, 0 violated, 19 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/mixed-dimension-embeddings-with-application#ran","syntology_url":"https://syntology.ai/paper/1909.11810","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.11810"}},"official":{"repos":["facebookresearch/dlrm"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/adaptive-factorization-network-learning","slug":"adaptive-factorization-network-learning","title":"Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions","date":"2019-09-07","arxiv_id":"1909.03276","repositories_listed":4,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/adaptive-factorization-network-learning#ran","syntology_url":"https://syntology.ai/paper/1909.03276","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.03276"}},"official":{"repos":["shenweichen/DeepCTR-Torch"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["named_in_paper"]}}},{"url":"/paper/fibinet-combining-feature-importance-and","slug":"fibinet-combining-feature-importance-and","title":"FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction","date":"2019-05-23","arxiv_id":"1905.09433","repositories_listed":31,"syntology":{"n":26,"n_ran":12,"n_constructed":0,"n_ran_checked":12,"n_instrument":0,"n_unverified":14,"n_honours":2,"n_violates":0,"n_no_contract":10,"n_pointer_only":3,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 2 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 14 unverified","sample_list":"/paper/fibinet-combining-feature-importance-and#ran","syntology_url":"https://syntology.ai/paper/1905.09433","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.09433"}},"official":null}},{"url":"/paper/practice-on-long-sequential-user-behavior","slug":"practice-on-long-sequential-user-behavior","title":"Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction","date":"2019-05-22","arxiv_id":"1905.09248","repositories_listed":2,"syntology":{"n":5,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/practice-on-long-sequential-user-behavior#ran","syntology_url":"https://syntology.ai/paper/1905.09248","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.09248"}},"official":{"repos":["UIC-Paper/MIMN"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/deep-session-interest-network-for-click","slug":"deep-session-interest-network-for-click","title":"Deep Session Interest Network for Click-Through Rate Prediction","date":"2019-05-16","arxiv_id":"1905.06482","repositories_listed":7,"syntology":{"n":11,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/deep-session-interest-network-for-click#ran","syntology_url":"https://syntology.ai/paper/1905.06482","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.06482"}},"official":{"repos":["shenweichen/DSIN"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/behavior-sequence-transformer-for-e-commerce","slug":"behavior-sequence-transformer-for-e-commerce","title":"Behavior Sequence Transformer for E-commerce Recommendation in Alibaba","date":"2019-05-15","arxiv_id":"1905.06874","repositories_listed":9,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/behavior-sequence-transformer-for-e-commerce#ran","syntology_url":"https://syntology.ai/paper/1905.06874","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.06874"}},"official":null}},{"url":"/paper/190412575","slug":"190412575","title":"Knowledge Graph Convolutional Networks for Recommender Systems","date":"2019-03-18","arxiv_id":"1904.12575","repositories_listed":8,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/190412575#ran","syntology_url":"https://syntology.ai/paper/1904.12575","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.12575"}},"official":{"repos":["hwwang55/KGCN"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/autoint-automatic-feature-interaction","slug":"autoint-automatic-feature-interaction","title":"AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks","date":"2018-10-29","arxiv_id":"1810.11921","repositories_listed":19,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/autoint-automatic-feature-interaction#ran","syntology_url":"https://syntology.ai/paper/1810.11921","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.11921"}},"official":{"repos":["DeepGraphLearning/RecommenderSystems"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/deep-interest-evolution-network-for-click","slug":"deep-interest-evolution-network-for-click","title":"Deep Interest Evolution Network for Click-Through Rate Prediction","date":"2018-09-11","arxiv_id":"1809.03672","repositories_listed":15,"syntology":{"n":14,"n_ran":12,"n_constructed":0,"n_ran_checked":12,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":0,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/deep-interest-evolution-network-for-click#ran","syntology_url":"https://syntology.ai/paper/1809.03672","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1809.03672"}},"official":{"repos":["mouna99/dien"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/deepfm-an-end-to-end-wide-deep-learning","slug":"deepfm-an-end-to-end-wide-deep-learning","title":"DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction","date":"2018-04-12","arxiv_id":"1804.04950","repositories_listed":8,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/deepfm-an-end-to-end-wide-deep-learning#ran","syntology_url":"https://syntology.ai/paper/1804.04950","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1804.04950"}},"official":null}},{"url":"/paper/xdeepfm-combining-explicit-and-implicit","slug":"xdeepfm-combining-explicit-and-implicit","title":"xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems","date":"2018-03-14","arxiv_id":"1803.05170","repositories_listed":19,"syntology":{"n":15,"n_ran":12,"n_constructed":0,"n_ran_checked":11,"n_instrument":1,"n_unverified":3,"n_honours":2,"n_violates":0,"n_no_contract":9,"n_pointer_only":3,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 2 honoured, 0 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/xdeepfm-combining-explicit-and-implicit#ran","syntology_url":"https://syntology.ai/paper/1803.05170","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.05170"}},"official":{"repos":["Leavingseason/xDeepFM"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/ripplenet-propagating-user-preferences-on-the","slug":"ripplenet-propagating-user-preferences-on-the","title":"RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems","date":"2018-03-09","arxiv_id":"1803.03467","repositories_listed":9,"syntology":{"n":7,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":4,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/ripplenet-propagating-user-preferences-on-the#ran","syntology_url":"https://syntology.ai/paper/1803.03467","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.03467"}},"official":{"repos":["hwwang55/RippleNet"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/deep-cross-network-for-ad-click-predictions","slug":"deep-cross-network-for-ad-click-predictions","title":"Deep & Cross Network for Ad Click Predictions","date":"2017-08-17","arxiv_id":"1708.05123","repositories_listed":16,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-cross-network-for-ad-click-predictions#ran","syntology_url":"https://syntology.ai/paper/1708.05123","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1708.05123"}},"official":null}},{"url":"/paper/deepfm-a-factorization-machine-based-neural","slug":"deepfm-a-factorization-machine-based-neural","title":"DeepFM: A Factorization-Machine based Neural Network for CTR Prediction","date":"2017-03-13","arxiv_id":"1703.04247","repositories_listed":23,"syntology":{"n":8,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":4,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/deepfm-a-factorization-machine-based-neural#ran","syntology_url":"https://syntology.ai/paper/1703.04247","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1703.04247"}},"official":{"repos":["xue-pai/FuxiCTR"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/wide-deep-learning-for-recommender-systems","slug":"wide-deep-learning-for-recommender-systems","title":"Wide & Deep Learning for Recommender Systems","date":"2016-06-24","arxiv_id":"1606.07792","repositories_listed":39,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":5,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/wide-deep-learning-for-recommender-systems#ran","syntology_url":"https://syntology.ai/paper/1606.07792","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1606.07792"}},"official":null}}],"record_sha256":"5245dad544ea5f642df1145840e235cfed7e3a36fc5b24a68275980a9949a0b9","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}