{"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/relational-reasoning/papers/2","list_of":"/task/relational-reasoning","task":"Relational Reasoning","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":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":5,"rows_per_page":100,"rows":[101,200],"of":483,"counts":{"archive_papers_tagged":483,"with_a_code_link":179,"where_syntology_ran_a_sample":58,"not_listed_spam_title":0,"listed":483,"listed_where_code_ran":58,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":52,"every_run_a_failure_of_syntologys_instrument":6,"listed_with_a_run_with_no_instrument_failure":52,"listed_every_run_a_failure_of_syntologys_instrument":6,"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/relational-reasoning","prev":"/task/relational-reasoning","next":"/task/relational-reasoning/papers/3","papers":[{"url":"/paper/coresets-for-relational-data-and-the","slug":"coresets-for-relational-data-and-the","title":"Coresets for Relational Data and The Applications","date":"2022-10-09","arxiv_id":"2210.04249","repositories_listed":1,"syntology":null},{"url":"/paper/relational-program-synthesis-with-numerical","slug":"relational-program-synthesis-with-numerical","title":"Relational program synthesis with numerical reasoning","date":"2022-10-03","arxiv_id":"2210.00764","repositories_listed":1,"syntology":null},{"url":"/paper/vgstore-a-multimodal-extension-to-sparql-for","slug":"vgstore-a-multimodal-extension-to-sparql-for","title":"VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph","date":"2022-09-07","arxiv_id":"2209.02981","repositories_listed":1,"syntology":null},{"url":"/paper/semantic-novelty-detection-via-relational","slug":"semantic-novelty-detection-via-relational","title":"Semantic Novelty Detection via Relational Reasoning","date":"2022-07-18","arxiv_id":"2207.08699","repositories_listed":1,"syntology":null},{"url":"/paper/video-dialog-as-conversation-about-objects","slug":"video-dialog-as-conversation-about-objects","title":"Video Dialog as Conversation about Objects Living in Space-Time","date":"2022-07-08","arxiv_id":"2207.03656","repositories_listed":1,"syntology":null},{"url":"/paper/computer-aided-tuberculosis-diagnosis-with","slug":"computer-aided-tuberculosis-diagnosis-with","title":"Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance","date":"2022-07-01","arxiv_id":"2207.00251","repositories_listed":1,"syntology":null},{"url":"/paper/specializing-pre-trained-language-models-for","slug":"specializing-pre-trained-language-models-for","title":"Specializing Pre-trained Language Models for Better Relational Reasoning via Network Pruning","date":"2022-07-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-group-aware-networks-for-multi-agent","slug":"dynamic-group-aware-networks-for-multi-agent","title":"Dynamic-Group-Aware Networks for Multi-Agent Trajectory Prediction with Relational Reasoning","date":"2022-06-27","arxiv_id":"2206.13114","repositories_listed":1,"syntology":null},{"url":"/paper/leveraging-relational-information-for-1","slug":"leveraging-relational-information-for-1","title":"Leveraging Relational Information for Learning Weakly Disentangled Representations","date":"2022-05-20","arxiv_id":"2205.10056","repositories_listed":1,"syntology":null},{"url":"/paper/r5-rule-discovery-with-reinforced-and-1","slug":"r5-rule-discovery-with-reinforced-and-1","title":"R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning","date":"2022-05-13","arxiv_id":"2205.06454","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 1 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; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/r5-rule-discovery-with-reinforced-and-1#ran","syntology_url":"https://syntology.ai/paper/2205.06454","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.06454"}},"official":{"repos":["sluxsr/r5_graph_reasoning"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/groupnet-multiscale-hypergraph-neural","slug":"groupnet-multiscale-hypergraph-neural","title":"GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning","date":"2022-04-19","arxiv_id":"2204.08770","repositories_listed":1,"syntology":{"n":19,"n_ran":12,"n_constructed":6,"n_ran_checked":7,"n_instrument":5,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"12 ran (of which 6 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 5 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/groupnet-multiscale-hypergraph-neural#ran","syntology_url":"https://syntology.ai/paper/2204.08770","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.08770"}},"official":{"repos":["mediabrain-sjtu/groupnet"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":6,"n_ran_no_instrument_failure":7,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/optimal-quadratic-binding-for-relational","slug":"optimal-quadratic-binding-for-relational","title":"Optimal quadratic binding for relational reasoning in vector symbolic neural architectures","date":"2022-04-14","arxiv_id":"2204.07186","repositories_listed":1,"syntology":null},{"url":"/paper/learning-to-reason-deductively-math-word","slug":"learning-to-reason-deductively-math-word","title":"Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction","date":"2022-03-19","arxiv_id":"2203.10316","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":1,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":3,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-to-reason-deductively-math-word#ran","syntology_url":"https://syntology.ai/paper/2203.10316","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.10316"}},"official":{"repos":["allanj/deductive-mwp"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/darer-dual-task-temporal-relational-recurrent","slug":"darer-dual-task-temporal-relational-recurrent","title":"DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition","date":"2022-03-08","arxiv_id":"2203.03856","repositories_listed":1,"syntology":null},{"url":"/paper/core-text-improving-scene-text-detection-with","slug":"core-text-improving-scene-text-detection-with","title":"CORE-Text: Improving Scene Text Detection with Contrastive Relational Reasoning","date":"2021-12-14","arxiv_id":"2112.07513","repositories_listed":1,"syntology":null},{"url":"/paper/composer-compositional-learning-of-group","slug":"composer-compositional-learning-of-group","title":"COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality","date":"2021-12-11","arxiv_id":"2112.05892","repositories_listed":1,"syntology":null},{"url":"/paper/systematic-generalization-with-edge-1","slug":"systematic-generalization-with-edge-1","title":"Systematic Generalization with Edge Transformers","date":"2021-12-01","arxiv_id":"2112.00578","repositories_listed":1,"syntology":null},{"url":"/paper/orchard-a-benchmark-for-measuring-systematic","slug":"orchard-a-benchmark-for-measuring-systematic","title":"ORCHARD: A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical Reasoning","date":"2021-11-28","arxiv_id":"2111.14034","repositories_listed":1,"syntology":null},{"url":"/paper/topological-relational-learning-on-graphs","slug":"topological-relational-learning-on-graphs","title":"Topological Relational Learning on Graphs","date":"2021-10-29","arxiv_id":"2110.15529","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"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) · 0 unverified","sample_list":"/paper/topological-relational-learning-on-graphs#ran","syntology_url":"https://syntology.ai/paper/2110.15529","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.15529"}},"official":{"repos":["tri-gnn/tri-gnn"],"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"]}}},{"url":"/paper/propagation-on-multi-relational-graphs-for","slug":"propagation-on-multi-relational-graphs-for","title":"Propagation on Multi-relational Graphs for Node Regression","date":"2021-10-15","arxiv_id":"2110.08185","repositories_listed":1,"syntology":null},{"url":"/paper/relation-prediction-as-an-auxiliary-training","slug":"relation-prediction-as-an-auxiliary-training","title":"Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations","date":"2021-10-06","arxiv_id":"2110.02834","repositories_listed":1,"syntology":null},{"url":"/paper/identifying-morality-frames-in-political","slug":"identifying-morality-frames-in-political","title":"Identifying Morality Frames in Political Tweets using Relational Learning","date":"2021-09-09","arxiv_id":"2109.04535","repositories_listed":1,"syntology":null},{"url":"/paper/probing-cross-modal-representations-in-multi","slug":"probing-cross-modal-representations-in-multi","title":"Probing Cross-Modal Representations in Multi-Step Relational Reasoning","date":"2021-08-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/dualvgr-a-dual-visual-graph-reasoning-unit","slug":"dualvgr-a-dual-visual-graph-reasoning-unit","title":"DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question Answering","date":"2021-07-10","arxiv_id":"2107.04768","repositories_listed":1,"syntology":null},{"url":"/paper/relational-vae-a-continuous-latent-variable","slug":"relational-vae-a-continuous-latent-variable","title":"Relational VAE: A Continuous Latent Variable Model for Graph Structured Data","date":"2021-06-30","arxiv_id":"2106.16049","repositories_listed":1,"syntology":null},{"url":"/paper/complementary-structure-learning-neural","slug":"complementary-structure-learning-neural","title":"Complementary Structure-Learning Neural Networks for Relational Reasoning","date":"2021-05-19","arxiv_id":"2105.08944","repositories_listed":1,"syntology":null},{"url":"/paper/relational-learning-with-gated-and-attentive","slug":"relational-learning-with-gated-and-attentive","title":"Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion","date":"2021-04-27","arxiv_id":"2104.13095","repositories_listed":1,"syntology":null},{"url":"/paper/prototypical-representation-learning-for-1","slug":"prototypical-representation-learning-for-1","title":"Prototypical Representation Learning for Relation Extraction","date":"2021-03-22","arxiv_id":"2103.11647","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 1 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; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/prototypical-representation-learning-for-1#ran","syntology_url":"https://syntology.ai/paper/2103.11647","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.11647"}},"official":{"repos":["Alibaba-NLP/ProtoRE"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/inductive-relation-prediction-by-bert","slug":"inductive-relation-prediction-by-bert","title":"Inductive Relation Prediction by BERT","date":"2021-03-12","arxiv_id":"2103.07102","repositories_listed":1,"syntology":null},{"url":"/paper/learning-symbolic-operators-for-task-and","slug":"learning-symbolic-operators-for-task-and","title":"Learning Symbolic Operators for Task and Motion Planning","date":"2021-02-28","arxiv_id":"2103.00589","repositories_listed":1,"syntology":null},{"url":"/paper/graphlog-a-benchmark-for-measuring-logical","slug":"graphlog-a-benchmark-for-measuring-logical","title":"GraphLog: A Benchmark for Measuring Logical Generalization in Graph Neural Networks","date":"2021-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/erica-improving-entity-and-relation","slug":"erica-improving-entity-and-relation","title":"ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning","date":"2020-12-30","arxiv_id":"2012.15022","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"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) · 1 unverified","sample_list":"/paper/erica-improving-entity-and-relation#ran","syntology_url":"https://syntology.ai/paper/2012.15022","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2012.15022"}},"official":{"repos":["thunlp/ERICA"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/open-ended-multi-modal-relational-reason-for","slug":"open-ended-multi-modal-relational-reason-for","title":"Open-Ended Multi-Modal Relational Reasoning for Video Question Answering","date":"2020-12-01","arxiv_id":"2012.00822","repositories_listed":1,"syntology":null},{"url":"/paper/self-supervised-time-series-representation-1","slug":"self-supervised-time-series-representation-1","title":"Self-Supervised Time Series Representation Learning by Inter-Intra Relational Reasoning","date":"2020-11-27","arxiv_id":"2011.13548","repositories_listed":1,"syntology":null},{"url":"/paper/play-fair-frame-attributions-in-video-models","slug":"play-fair-frame-attributions-in-video-models","title":"Play Fair: Frame Attributions in Video Models","date":"2020-11-24","arxiv_id":"2011.12372","repositories_listed":1,"syntology":null},{"url":"/paper/modeling-content-and-context-with-deep","slug":"modeling-content-and-context-with-deep","title":"Modeling Content and Context with Deep Relational Learning","date":"2020-10-20","arxiv_id":"2010.10453","repositories_listed":1,"syntology":null},{"url":"/paper/bayrel-bayesian-relational-learning-for-multi","slug":"bayrel-bayesian-relational-learning-for-multi","title":"BayReL: Bayesian Relational Learning for Multi-omics Data Integration","date":"2020-10-12","arxiv_id":"2010.05895","repositories_listed":1,"syntology":null},{"url":"/paper/rvl-bert-visual-relationship-detection-with","slug":"rvl-bert-visual-relationship-detection-with","title":"Visual Relationship Detection with Visual-Linguistic Knowledge from Multimodal Representations","date":"2020-09-10","arxiv_id":"2009.04965","repositories_listed":1,"syntology":null},{"url":"/paper/lowfer-low-rank-bilinear-pooling-for-link","slug":"lowfer-low-rank-bilinear-pooling-for-link","title":"LowFER: Low-rank Bilinear Pooling for Link Prediction","date":"2020-08-25","arxiv_id":"2008.10858","repositories_listed":1,"syntology":{"n":3,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 3 unverified","sample_list":"/paper/lowfer-low-rank-bilinear-pooling-for-link#ran","syntology_url":"https://syntology.ai/paper/2008.10858","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.10858"}},"official":{"repos":["suamin/LowFER"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":[]}}},{"url":"/paper/distributed-memory-based-self-supervised","slug":"distributed-memory-based-self-supervised","title":"Distributed Associative Memory Network with Memory Refreshing Loss","date":"2020-07-21","arxiv_id":"2007.10637","repositories_listed":1,"syntology":{"n":9,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"5 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; 1 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/distributed-memory-based-self-supervised#ran","syntology_url":"https://syntology.ai/paper/2007.10637","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.10637"}},"official":{"repos":["taewonpark/DAM"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/graph-based-social-relation-reasoning","slug":"graph-based-social-relation-reasoning","title":"Graph-Based Social Relation Reasoning","date":"2020-07-15","arxiv_id":"2007.07453","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/graph-based-social-relation-reasoning#ran","syntology_url":"https://syntology.ai/paper/2007.07453","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.07453"}},"official":{"repos":["Li-Wanhua/GR2N"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/relational-reasoning-and-generalization-using","slug":"relational-reasoning-and-generalization-using","title":"Relational reasoning and generalization using non-symbolic neural networks","date":"2020-06-14","arxiv_id":"2006.07968","repositories_listed":1,"syntology":null},{"url":"/paper/explaining-local-global-and-higher-order","slug":"explaining-local-global-and-higher-order","title":"Explaining Local, Global, And Higher-Order Interactions In Deep Learning","date":"2020-06-12","arxiv_id":"2006.08601","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"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) · 0 unverified","sample_list":"/paper/explaining-local-global-and-higher-order#ran","syntology_url":"https://syntology.ai/paper/2006.08601","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.08601"}},"official":{"repos":["slerman12/ExplainingInteractions"],"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"]}}},{"url":"/paper/self-supervised-relational-reasoning-for","slug":"self-supervised-relational-reasoning-for","title":"Self-Supervised Relational Reasoning for Representation Learning","date":"2020-06-10","arxiv_id":"2006.05849","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"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 1 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; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/self-supervised-relational-reasoning-for#ran","syntology_url":"https://syntology.ai/paper/2006.05849","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.05849"}},"official":{"repos":["mpatacchiola/self-supervised-relational-reasoning"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/evaluating-logical-generalization-in-graph","slug":"evaluating-logical-generalization-in-graph","title":"Evaluating Logical Generalization in Graph Neural Networks","date":"2020-03-14","arxiv_id":"2003.06560","repositories_listed":1,"syntology":null},{"url":"/paper/set-structured-latent-representations","slug":"set-structured-latent-representations","title":"Better Set Representations For Relational Reasoning","date":"2020-03-09","arxiv_id":"2003.04448","repositories_listed":1,"syntology":null},{"url":"/paper/self-assttentive-associative-memory","slug":"self-assttentive-associative-memory","title":"Self-Attentive Associative Memory","date":"2020-02-10","arxiv_id":"2002.03519","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/self-assttentive-associative-memory#ran","syntology_url":"https://syntology.ai/paper/2002.03519","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.03519"}},"official":{"repos":["thaihungle/SAM"],"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/a-survey-on-knowledge-graphs-representation","slug":"a-survey-on-knowledge-graphs-representation","title":"A Survey on Knowledge Graphs: Representation, Acquisition and Applications","date":"2020-02-02","arxiv_id":"2002.00388","repositories_listed":1,"syntology":null},{"url":"/paper/quantum-embedding-of-knowledge-for-reasoning","slug":"quantum-embedding-of-knowledge-for-reasoning","title":"Quantum Embedding of Knowledge for Reasoning","date":"2019-12-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/interaction-relational-network-for-mutual","slug":"interaction-relational-network-for-mutual","title":"Interaction Relational Network for Mutual Action Recognition","date":"2019-10-11","arxiv_id":"1910.04963","repositories_listed":1,"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":0,"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/interaction-relational-network-for-mutual#ran","syntology_url":"https://syntology.ai/paper/1910.04963","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.04963"}},"official":{"repos":["mauriciolp/inter-rel-net"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/relational-learning-for-joint-head-and-human","slug":"relational-learning-for-joint-head-and-human","title":"Relational Learning for Joint Head and Human Detection","date":"2019-09-24","arxiv_id":"1909.10674","repositories_listed":1,"syntology":null},{"url":"/paper/rudas-synthetic-datasets-for-rule-learning","slug":"rudas-synthetic-datasets-for-rule-learning","title":"RuDaS: Synthetic Datasets for Rule Learning and Evaluation Tools","date":"2019-09-16","arxiv_id":"1909.07095","repositories_listed":1,"syntology":null},{"url":"/paper/parn-position-aware-relation-networks-for-few","slug":"parn-position-aware-relation-networks-for-few","title":"PARN: Position-Aware Relation Networks for Few-Shot Learning","date":"2019-09-10","arxiv_id":"1909.04332","repositories_listed":1,"syntology":null},{"url":"/paper/relationships-from-entity-stream","slug":"relationships-from-entity-stream","title":"Relationships from Entity Stream","date":"2019-09-07","arxiv_id":"1909.03315","repositories_listed":1,"syntology":null},{"url":"/paper/meta-relational-learning-for-few-shot-link","slug":"meta-relational-learning-for-few-shot-link","title":"Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs","date":"2019-09-04","arxiv_id":"1909.01515","repositories_listed":1,"syntology":null},{"url":"/paper/relation-network-for-multi-label-aerial-image","slug":"relation-network-for-multi-label-aerial-image","title":"Relation Network for Multi-label Aerial Image Classification","date":"2019-07-16","arxiv_id":"1907.07274","repositories_listed":1,"syntology":null},{"url":"/paper/cognitive-knowledge-graph-reasoning-for-one","slug":"cognitive-knowledge-graph-reasoning-for-one","title":"Cognitive Knowledge Graph Reasoning for One-shot Relational Learning","date":"2019-06-13","arxiv_id":"1906.05489","repositories_listed":1,"syntology":null},{"url":"/paper/wikidatasets-standardized-sub-graphs-from","slug":"wikidatasets-standardized-sub-graphs-from","title":"WikiDataSets: Standardized sub-graphs from Wikidata","date":"2019-06-11","arxiv_id":"1906.04536","repositories_listed":1,"syntology":null},{"url":"/paper/gmnn-graph-markov-neural-networks","slug":"gmnn-graph-markov-neural-networks","title":"GMNN: Graph Markov Neural Networks","date":"2019-05-15","arxiv_id":"1905.06214","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/gmnn-graph-markov-neural-networks#ran","syntology_url":"https://syntology.ai/paper/1905.06214","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.06214"}},"official":null}},{"url":"/paper/the-relational-processing-limits-of-classic","slug":"the-relational-processing-limits-of-classic","title":"The relational processing limits of classic and contemporary neural network models of language processing","date":"2019-05-12","arxiv_id":"1905.05708","repositories_listed":1,"syntology":null},{"url":"/paper/language-conditioned-graph-networks-for","slug":"language-conditioned-graph-networks-for","title":"Language-Conditioned Graph Networks for Relational Reasoning","date":"2019-05-10","arxiv_id":"1905.04405","repositories_listed":1,"syntology":{"n":10,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":7,"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) · 7 unverified","sample_list":"/paper/language-conditioned-graph-networks-for#ran","syntology_url":"https://syntology.ai/paper/1905.04405","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.04405"}},"official":null}},{"url":"/paper/object-oriented-dynamics-learning-through","slug":"object-oriented-dynamics-learning-through","title":"Object-Oriented Dynamics Learning through Multi-Level Abstraction","date":"2019-04-16","arxiv_id":"1904.07482","repositories_listed":1,"syntology":{"n":6,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 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; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/object-oriented-dynamics-learning-through#ran","syntology_url":"https://syntology.ai/paper/1904.07482","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.07482"}},"official":null}},{"url":"/paper/murel-multimodal-relational-reasoning-for","slug":"murel-multimodal-relational-reasoning-for","title":"MUREL: Multimodal Relational Reasoning for Visual Question Answering","date":"2019-02-25","arxiv_id":"1902.09487","repositories_listed":1,"syntology":null},{"url":"/paper/graph-neural-networks-with-generated","slug":"graph-neural-networks-with-generated","title":"Graph Neural Networks with Generated Parameters for Relation Extraction","date":"2019-02-02","arxiv_id":"1902.00756","repositories_listed":1,"syntology":null},{"url":"/paper/interpretable-preference-learning-a-game","slug":"interpretable-preference-learning-a-game","title":"Interpretable preference learning: a game theoretic framework for large margin on-line feature and rule learning","date":"2018-12-19","arxiv_id":"1812.07895","repositories_listed":1,"syntology":null},{"url":"/paper/one-shot-relational-learning-for-knowledge","slug":"one-shot-relational-learning-for-knowledge","title":"One-Shot Relational Learning for Knowledge Graphs","date":"2018-08-27","arxiv_id":"1808.09040","repositories_listed":1,"syntology":null},{"url":"/paper/on-embeddings-as-an-alternative-paradigm-for","slug":"on-embeddings-as-an-alternative-paradigm-for","title":"A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning","date":"2018-06-29","arxiv_id":"1806.11391","repositories_listed":1,"syntology":null},{"url":"/paper/scalable-label-propagation-for-multi","slug":"scalable-label-propagation-for-multi","title":"Scalable Label Propagation for Multi-relational Learning on the Tensor Product of Graphs","date":"2018-02-20","arxiv_id":"1802.07379","repositories_listed":1,"syntology":null},{"url":"/paper/recurrent-relational-networks-for-complex","slug":"recurrent-relational-networks-for-complex","title":"Recurrent Relational Networks for complex relational reasoning","date":"2018-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/relnn-a-deep-neural-model-for-relational","slug":"relnn-a-deep-neural-model-for-relational","title":"RelNN: A Deep Neural Model for Relational Learning","date":"2017-12-07","arxiv_id":"1712.02831","repositories_listed":1,"syntology":null},{"url":"/paper/mandolin-a-knowledge-discovery-framework-for","slug":"mandolin-a-knowledge-discovery-framework-for","title":"Mandolin: A Knowledge Discovery Framework for the Web of Data","date":"2017-11-03","arxiv_id":"1711.01283","repositories_listed":1,"syntology":null},{"url":"/paper/on-inductive-abilities-of-latent-factor","slug":"on-inductive-abilities-of-latent-factor","title":"On Inductive Abilities of Latent Factor Models for Relational Learning","date":"2017-09-17","arxiv_id":"1709.05666","repositories_listed":1,"syntology":null},{"url":"/paper/adversarial-sets-for-regularising-neural-link","slug":"adversarial-sets-for-regularising-neural-link","title":"Adversarial Sets for Regularising Neural Link Predictors","date":"2017-07-24","arxiv_id":"1707.07596","repositories_listed":1,"syntology":null},{"url":"/paper/robust-face-tracking-using-multiple","slug":"robust-face-tracking-using-multiple","title":"Robust Face Tracking using Multiple Appearance Models and Graph Relational Learning","date":"2017-06-29","arxiv_id":"1706.09806","repositories_listed":1,"syntology":null},{"url":"/paper/logic-tensor-networks-for-semantic-image","slug":"logic-tensor-networks-for-semantic-image","title":"Logic Tensor Networks for Semantic Image Interpretation","date":"2017-05-24","arxiv_id":"1705.08968","repositories_listed":1,"syntology":null},{"url":"/paper/graph-based-relational-features-for","slug":"graph-based-relational-features-for","title":"Graph Based Relational Features for Collective Classification","date":"2017-02-09","arxiv_id":"1702.02817","repositories_listed":1,"syntology":null},{"url":"/paper/column-networks-for-collective-classification","slug":"column-networks-for-collective-classification","title":"Column Networks for Collective Classification","date":"2016-09-15","arxiv_id":"1609.04508","repositories_listed":1,"syntology":null},{"url":"/paper/osl-online-structure-learning-using","slug":"osl-online-structure-learning-using","title":"OSL𝛼: Online Structure Learning Using Background Knowledge Axiomatization","date":"2016-09-04","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/lifted-relational-neural-networks","slug":"lifted-relational-neural-networks","title":"Lifted Relational Neural Networks","date":"2015-08-20","arxiv_id":"1508.05128","repositories_listed":1,"syntology":null},{"url":null,"slug":"freeq-graph-free-form-querying-with-semantic","title":"FreeQ-Graph: Free-form Querying with Semantic Consistent Scene Graph for 3D Scene Understanding","date":"2025-06-16","arxiv_id":"2506.13629","repositories_listed":0,"syntology":null},{"url":null,"slug":"2506-10527","title":"LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs","date":"2025-06-12","arxiv_id":"2506.10527","repositories_listed":0,"syntology":null},{"url":null,"slug":"2506-04289","title":"Relational reasoning and inductive bias in transformers trained on a transitive inference task","date":"2025-06-04","arxiv_id":"2506.04289","repositories_listed":0,"syntology":null},{"url":null,"slug":"modulm-enabling-modular-and-multimodal","title":"ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models","date":"2025-06-01","arxiv_id":"2506.00880","repositories_listed":0,"syntology":null},{"url":null,"slug":"2505-10604","title":"MIRAGE: A Multi-modal Benchmark for Spatial Perception, Reasoning, and Intelligence","date":"2025-05-15","arxiv_id":"2505.10604","repositories_listed":0,"syntology":null},{"url":null,"slug":"arbitrarily-applicable-same-opposite","title":"Arbitrarily Applicable Same/Opposite Relational Responding with NARS","date":"2025-05-11","arxiv_id":"2505.07079","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-neural-language-inference-via","title":"Boosting Neural Language Inference via Cascaded Interactive Reasoning","date":"2025-05-10","arxiv_id":"2505.06607","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-systematic-relational-reasoning","title":"Benchmarking Systematic Relational Reasoning with Large Language and Reasoning Models","date":"2025-03-30","arxiv_id":"2503.23487","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-to-vision-multi-graph-understanding-and","title":"Graph-to-Vision: Multi-graph Understanding and Reasoning using Vision-Language Models","date":"2025-03-27","arxiv_id":"2503.21435","repositories_listed":0,"syntology":null},{"url":null,"slug":"v-star-benchmarking-video-llms-on-video","title":"V-STaR: Benchmarking Video-LLMs on Video Spatio-Temporal Reasoning","date":"2025-03-14","arxiv_id":"2503.11495","repositories_listed":0,"syntology":null},{"url":null,"slug":"representational-alignment-with-chemical","title":"Representational Alignment with Chemical Induced Fit for Molecular Relational Learning","date":"2025-02-07","arxiv_id":"2502.07027","repositories_listed":0,"syntology":null},{"url":null,"slug":"reasoning-oriented-and-analogy-based-methods","title":"Reasoning-Oriented and Analogy-Based Methods for Locating and Editing in Zero-Shot Event-Relational Reasoning","date":"2025-01-01","arxiv_id":"2501.00803","repositories_listed":0,"syntology":null},{"url":null,"slug":"path-of-thoughts-extracting-and-following","title":"Path-of-Thoughts: Extracting and Following Paths for Robust Relational Reasoning with Large Language Models","date":"2024-12-23","arxiv_id":"2412.17963","repositories_listed":0,"syntology":null},{"url":null,"slug":"explicit-relational-reasoning-network-for","title":"Explicit Relational Reasoning Network for Scene Text Detection","date":"2024-12-19","arxiv_id":"2412.14692","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-guided-coarse-to-fine-fusion-network-for","title":"Text-Guided Coarse-to-Fine Fusion Network for Robust Remote Sensing Visual Question Answering","date":"2024-11-24","arxiv_id":"2411.15770","repositories_listed":0,"syntology":null},{"url":null,"slug":"financial-risk-assessment-via-long-term","title":"Financial Risk Assessment via Long-term Payment Behavior Sequence Folding","date":"2024-11-22","arxiv_id":"2411.15056","repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-linguistic-agent-towards-collaborative","title":"Visual-Linguistic Agent: Towards Collaborative Contextual Object Reasoning","date":"2024-11-15","arxiv_id":"2411.10252","repositories_listed":0,"syntology":null},{"url":null,"slug":"post-hoc-robustness-enhancement-in-graph","title":"Post-Hoc Robustness Enhancement in Graph Neural Networks with Conditional Random Fields","date":"2024-11-08","arxiv_id":"2411.05399","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-it-me-or-is-a-larger-than-b-uncovering-the","title":"Two pathways to resolve relational inconsistencies","date":"2024-10-30","arxiv_id":"2411.05809","repositories_listed":0,"syntology":null},{"url":null,"slug":"sold-reinforcement-learning-with-slot-object","title":"SOLD: Slot Object-Centric Latent Dynamics Models for Relational Manipulation Learning from Pixels","date":"2024-10-11","arxiv_id":"2410.08822","repositories_listed":0,"syntology":null},{"url":null,"slug":"shifting-the-human-ai-relationship-toward-a","title":"Shifting the Human-AI Relationship: Toward a Dynamic Relational Learning-Partner Model","date":"2024-10-07","arxiv_id":"2410.11864","repositories_listed":0,"syntology":null}],"record_sha256":"fbd4bfbcd4587f6f7f9643cbb395fa9e7b2e7b0f9c69609f3387ca22a28b02af","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}