{"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/knowledge-graphs/papers/26","list_of":"/task/knowledge-graphs","task":"Knowledge Graphs","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":26,"pages_in_order":30,"rows_per_page":100,"rows":[2501,2600],"of":2974,"counts":{"archive_papers_tagged":2974,"with_a_code_link":1273,"where_syntology_ran_a_sample":234,"not_listed_spam_title":0,"listed":2974,"listed_where_code_ran":234,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":207,"every_run_a_failure_of_syntologys_instrument":27,"listed_with_a_run_with_no_instrument_failure":207,"listed_every_run_a_failure_of_syntologys_instrument":27,"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/knowledge-graphs","prev":"/task/knowledge-graphs/papers/25","next":"/task/knowledge-graphs/papers/27","papers":[{"url":null,"slug":"search-from-history-and-reason-for-future-two","title":"Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs","date":"2021-06-01","arxiv_id":"2106.00327","repositories_listed":0,"syntology":null},{"url":null,"slug":"wikipedia-entities-as-rendezvous-across","title":"Wikipedia Entities as Rendezvous across Languages: Grounding Multilingual Language Models by Predicting Wikipedia Hyperlinks","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"worldly-wise-wow-cross-lingual-knowledge","title":"Worldly Wise (WoW) - Cross-Lingual Knowledge Fusion for Fact-based Visual Spoken-Question Answering","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"path-based-knowledge-reasoning-with-textual","title":"Path-based knowledge reasoning with textual semantic information for medical knowledge graph completion","date":"2021-05-27","arxiv_id":"2105.13074","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-medical-entity-retrieval-without","title":"Zero-shot Medical Entity Retrieval without Annotation: Learning From Rich Knowledge Graph Semantics","date":"2021-05-26","arxiv_id":"2105.12682","repositories_listed":0,"syntology":null},{"url":null,"slug":"belt-blockwise-missing-embedding-learning","title":"Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices","date":"2021-05-21","arxiv_id":"2105.10360","repositories_listed":0,"syntology":null},{"url":null,"slug":"itelos-building-reusable-knowledge-graphs","title":"iTelos -- Purpose Driven Knowledge Graph Generation","date":"2021-05-19","arxiv_id":"2105.09418","repositories_listed":0,"syntology":null},{"url":null,"slug":"kecrs-towards-knowledge-enriched","title":"KECRS: Towards Knowledge-Enriched Conversational Recommendation System","date":"2021-05-18","arxiv_id":"2105.08261","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-knowledge-embedding-fully-exploited-in","title":"Is Knowledge Embedding Fully Exploited in Language Understanding? An Empirical Study","date":"2021-05-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-symbolic-commonsense-reasoner-with","title":"Neural-Symbolic Commonsense Reasoner with Relation Predictors","date":"2021-05-14","arxiv_id":"2105.06717","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-commonsense-knowledge-graph-in","title":"Incorporating Commonsense Knowledge Graph in Pretrained Models for Social Commonsense Tasks","date":"2021-05-12","arxiv_id":"2105.05457","repositories_listed":0,"syntology":null},{"url":null,"slug":"thematic-recommendations-on-knowledge-graphs","title":"Thematic recommendations on knowledge graphs using multilayer networks","date":"2021-05-12","arxiv_id":"2105.05733","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-based-review-generation-by","title":"Knowledge-based Review Generation by Coherence Enhanced Text Planning","date":"2021-05-09","arxiv_id":"2105.03815","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-learning-a-survey","title":"Graph Learning: A Survey","date":"2021-05-03","arxiv_id":"2105.00696","repositories_listed":0,"syntology":null},{"url":null,"slug":"billion-scale-pre-trained-e-commerce-product","title":"Billion-scale Pre-trained E-commerce Product Knowledge Graph Model","date":"2021-05-02","arxiv_id":"2105.00388","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-knowledge-enhanced-learning-and-semantic","title":"A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking","date":"2021-04-27","arxiv_id":"2104.13046","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-knowledge-graphs-validation-through","title":"Towards Knowledge Graphs Validation through Weighted Knowledge Sources","date":"2021-04-26","arxiv_id":"2104.12622","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-transitivity-constraints-for","title":"Exploiting Transitivity Constraints for Entity Matching in Knowledge Graphs","date":"2021-04-22","arxiv_id":"2104.12589","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixed-curvature-multi-relational-graph-neural","title":"Mixed-Curvature Multi-Relational Graph Neural Network for Knowledge Graph Completion","date":"2021-04-19","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"membership-inference-attacks-on-knowledge","title":"Membership Inference Attacks on Knowledge Graphs","date":"2021-04-16","arxiv_id":"2104.08273","repositories_listed":0,"syntology":null},{"url":null,"slug":"applying-personal-knowledge-graphs-to-health","title":"Applying Personal Knowledge Graphs to Health","date":"2021-04-15","arxiv_id":"2104.07587","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-representation-learning-for-scientific","title":"On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs","date":"2021-04-12","arxiv_id":"2104.05866","repositories_listed":0,"syntology":null},{"url":null,"slug":"edge-enriching-knowledge-graph-embeddings","title":"Edge: Enriching Knowledge Graph Embeddings with External Text","date":"2021-04-11","arxiv_id":"2104.04909","repositories_listed":0,"syntology":null},{"url":null,"slug":"adcofe-advanced-contextual-feature-extraction","title":"AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification","date":"2021-04-09","arxiv_id":"2104.04517","repositories_listed":0,"syntology":null},{"url":null,"slug":"ki-bert-infusing-knowledge-context-for-better","title":"KI-BERT: Infusing Knowledge Context for Better Language and Domain Understanding","date":"2021-04-09","arxiv_id":"2104.08145","repositories_listed":0,"syntology":null},{"url":null,"slug":"coco-ex-a-tool-for-linking-concepts-from","title":"COCO-EX: A Tool for Linking Concepts from Texts to ConceptNet","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"complex-question-answering-on-knowledge","title":"Complex Question Answering on knowledge graphs using machine translation and multi-task learning","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"serag-semantic-entity-retrieval-from-arabic","title":"SERAG: Semantic Entity Retrieval from Arabic Knowledge Graphs","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"entity-context-graph-learning-entity","title":"Entity Context Graph: Learning Entity Representations fromSemi-Structured Textual Sources on the Web","date":"2021-03-29","arxiv_id":"2103.15950","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-connections-beyond-knowledge","title":"Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehension","date":"2021-03-26","arxiv_id":"2103.14443","repositories_listed":0,"syntology":null},{"url":null,"slug":"chronor-rotation-based-temporal-knowledge","title":"ChronoR: Rotation Based Temporal Knowledge Graph Embedding","date":"2021-03-18","arxiv_id":"2103.10379","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-paper-recommendation-method-empowered","title":"A Novel Paper Recommendation Method Empowered by Knowledge Graph: for Research Beginners","date":"2021-03-16","arxiv_id":"2103.08819","repositories_listed":0,"syntology":null},{"url":null,"slug":"kgsynnet-a-novel-entity-synonyms-discovery","title":"KGSynNet: A Novel Entity Synonyms Discovery Framework with Knowledge Graph","date":"2021-03-16","arxiv_id":"2103.08893","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-a-personal-health-library-enabled","title":"Using a Personal Health Library-Enabled mHealth Recommender System for Self-Management of Diabetes Among Underserved Populations: Use Case for Knowledge Graphs and Linked Data","date":"2021-03-16","arxiv_id":"2103.09311","repositories_listed":0,"syntology":null},{"url":null,"slug":"iwarded-a-system-for-benchmarking-datalog","title":"iWarded: A System for Benchmarking Datalog+/- Reasoning (technical report)","date":"2021-03-15","arxiv_id":"2103.08588","repositories_listed":0,"syntology":null},{"url":null,"slug":"finmatcher-at-finsim-2-hypernym-detection-in","title":"FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs","date":"2021-03-02","arxiv_id":"2103.01576","repositories_listed":0,"syntology":null},{"url":null,"slug":"technical-report-on-data-integration-and","title":"Technical Report on Data Integration and Preparation","date":"2021-03-02","arxiv_id":"2103.01986","repositories_listed":0,"syntology":null},{"url":null,"slug":"bert-based-knowledge-extraction-method-of","title":"BERT-based knowledge extraction method of unstructured domain text","date":"2021-03-01","arxiv_id":"2103.00728","repositories_listed":0,"syntology":null},{"url":null,"slug":"approximate-knowledge-graph-query-answering","title":"Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification","date":"2021-02-22","arxiv_id":"2102.11389","repositories_listed":0,"syntology":null},{"url":null,"slug":"lightcake-a-lightweight-framework-for-context","title":"LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding","date":"2021-02-22","arxiv_id":"2102.10826","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrakg-contrastive-based-transfer-learning","title":"Learning Visual Models using a Knowledge Graph as a Trainer","date":"2021-02-17","arxiv_id":"2102.08747","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-path-free-representation-learning-on","title":"Meta-Path-Free Representation Learning on Heterogeneous Networks","date":"2021-02-16","arxiv_id":"2102.08120","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-metamodel-and-framework-for-artificial","title":"A Metamodel and Framework for Artificial General Intelligence From Theory to Practice","date":"2021-02-11","arxiv_id":"2102.06112","repositories_listed":0,"syntology":null},{"url":null,"slug":"analysing-the-requirements-for-an-open","title":"Analysing the Requirements for an Open Research Knowledge Graph: Use Cases, Quality Requirements and Construction Strategies","date":"2021-02-11","arxiv_id":"2102.06021","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-extraction-from-co-occurring","title":"Information Extraction From Co-Occurring Similar Entities","date":"2021-02-10","arxiv_id":"2102.05444","repositories_listed":0,"syntology":null},{"url":"/paper/information-prediction-using-knowledge-graphs","slug":"information-prediction-using-knowledge-graphs","title":"TINKER: A framework for Open source Cyberthreat Intelligence","date":"2021-02-10","arxiv_id":"2102.05571","repositories_listed":0,"syntology":null},{"url":null,"slug":"malware-knowledge-graph-generation","title":"Malware Knowledge Graph Generation","date":"2021-02-10","arxiv_id":"2102.05583","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-visual-reasoning-by-exploiting-the","title":"Improving Scene Graph Classification by Exploiting Knowledge from Texts","date":"2021-02-09","arxiv_id":"2102.04760","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-fake-cyber-threat-intelligence","title":"Generating Fake Cyber Threat Intelligence Using Transformer-Based Models","date":"2021-02-08","arxiv_id":"2102.04351","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-limits-of-few-shot-link","title":"Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs","date":"2021-02-05","arxiv_id":"2102.03419","repositories_listed":0,"syntology":null},{"url":null,"slug":"materializing-knowledge-bases-via-trigger","title":"Materializing Knowledge Bases via Trigger Graphs","date":"2021-02-04","arxiv_id":"2102.02753","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-graph-representations","title":"Learning Graph Representations","date":"2021-02-03","arxiv_id":"2102.02026","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-pre-trained-language-models-and","title":"Combining pre-trained language models and structured knowledge","date":"2021-01-28","arxiv_id":"2101.12294","repositories_listed":0,"syntology":null},{"url":null,"slug":"mining-knowledge-graphs-from-incident-reports","title":"SoftNER: Mining Knowledge Graphs From Cloud Incidents","date":"2021-01-15","arxiv_id":"2101.05961","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-enhanced-top-k-recommendation-in","title":"Knowledge-Enhanced Top-K Recommendation in Poincaré Ball","date":"2021-01-13","arxiv_id":"2101.04852","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-knowledge-graphs-as-semantic-memory","title":"Dynamic Knowledge Graphs as Semantic Memory Model for Industrial Robots","date":"2021-01-04","arxiv_id":"2101.01099","repositories_listed":0,"syntology":null},{"url":null,"slug":"tensorizing-subgraph-search-in-the-supernet","title":"Topology-aware Tensor Decomposition for Meta-graph Learning","date":"2021-01-04","arxiv_id":"2101.01078","repositories_listed":0,"syntology":null},{"url":null,"slug":"box-to-box-transformation-for-modeling-joint","title":"Box-To-Box Transformation for Modeling Joint Hierarchies","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"differentiable-learning-of-graph-like-logical","title":"Differentiable Learning of Graph-like Logical Rules from Knowledge Graphs","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-subgraph-reasoning-for","title":"Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-contextualized-knowledge-graph","title":"Learning Contextualized Knowledge Graph Structures for Commonsense Reasoning","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-a-linking-between-wordnet-and","title":"Towards a Linking between WordNet and Wikidata","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"trace-tensorizing-and-generalizing-supernets","title":"TRACE: Tensorizing and Generalizing Supernets from Neural Architecture Search","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tracking-the-progress-of-language-models-by","title":"Tracking the progress of Language Models by extracting their underlying Knowledge Graphs","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generalized-relation-learning-with-semantic","title":"Generalized Relation Learning with Semantic Correlation Awareness for Link Prediction","date":"2020-12-22","arxiv_id":"2012.11957","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graphs-evolution-and-preservation-a","title":"Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019","date":"2020-12-22","arxiv_id":"2012.11936","repositories_listed":0,"syntology":null},{"url":null,"slug":"lexically-constrained-text-generation-through","title":"Lexically-constrained Text Generation through Commonsense Knowledge Extraction and Injection","date":"2020-12-19","arxiv_id":"2012.10813","repositories_listed":0,"syntology":null},{"url":null,"slug":"t-gap-learning-to-walk-across-time-for","title":"T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion","date":"2020-12-19","arxiv_id":"2012.10595","repositories_listed":0,"syntology":null},{"url":null,"slug":"biomedical-knowledge-graph-refinement-and","title":"Biomedical Knowledge Graph Refinement and Completion using Graph Representation Learning and Top-K Similarity Measure","date":"2020-12-18","arxiv_id":"2012.10540","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-adr-mechanisms-with-knowledge","title":"Investigating ADR mechanisms with knowledge graph mining and explainable AI","date":"2020-12-16","arxiv_id":"2012.09077","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graphs-in-manufacturing-and","title":"Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review","date":"2020-12-16","arxiv_id":"2012.09049","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graphs-and-natural-language","title":"Knowledge Graphs and Natural-Language Processing","date":"2020-12-15","arxiv_id":"2101.06111","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-annotation-for-tabular-data","title":"Semantic Annotation for Tabular Data","date":"2020-12-15","arxiv_id":"2012.08594","repositories_listed":0,"syntology":null},{"url":null,"slug":"context-enhanced-entity-and-relation","title":"Context-Enhanced Entity and Relation Embedding for Knowledge Graph Completion","date":"2020-12-13","arxiv_id":"2012.07011","repositories_listed":0,"syntology":null},{"url":null,"slug":"aligning-geographic-entities-from-historical","title":"Aligning geographic entities from historical maps for building knowledge graphs","date":"2020-12-05","arxiv_id":"2012.03069","repositories_listed":0,"syntology":null},{"url":null,"slug":"accelerating-road-sign-ground-truth","title":"Accelerating Road Sign Ground Truth Construction with Knowledge Graph and Machine Learning","date":"2020-12-04","arxiv_id":"2012.02672","repositories_listed":0,"syntology":null},{"url":null,"slug":"research-progress-of-news-recommendation","title":"Research Progress of News Recommendation Methods","date":"2020-12-04","arxiv_id":"2012.02360","repositories_listed":0,"syntology":null},{"url":null,"slug":"mapping-patterns-for-virtual-knowledge-graphs","title":"Mapping Patterns for Virtual Knowledge Graphs","date":"2020-12-03","arxiv_id":"2012.01917","repositories_listed":0,"syntology":null},{"url":null,"slug":"biomedical-knowledge-graph-refinement-with","title":"Biomedical Knowledge Graph Refinement with Embedding and Logic Rules","date":"2020-12-02","arxiv_id":"2012.01031","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-high-precision-pipeline-for-financial","title":"A High Precision Pipeline for Financial Knowledge Graph Construction","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cn-hit-it-nlp-at-semeval-2020-task-4-enhanced","title":"CN-HIT-IT.NLP at SemEval-2020 Task 4: Enhanced Language Representation with Multiple Knowledge Triples","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-attention-network-for-cross-lingual","title":"Dual Attention Network for Cross-lingual Entity Alignment","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-enhanced-natural-language-inference","title":"Knowledge-Enhanced Natural Language Inference Based on Knowledge Graphs","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mathcal-p-2-a-plan-and-pretrain-approach-for","title":"{\\mathcal{P}^2}: A Plan-and-Pretrain Approach for Knowledge Graph-to-Text Generation","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-fact-checking-by-counter","title":"Unsupervised Fact Checking by Counter-Weighted Positive and Negative Evidential Paths in A Knowledge Graph","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"relation-clustering-in-narrative-knowledge","title":"Relation Clustering in Narrative Knowledge Graphs","date":"2020-11-27","arxiv_id":"2011.13647","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-transferable-method-for-named-entity","title":"Domain-Transferable Method for Named Entity Recognition Task","date":"2020-11-24","arxiv_id":"2011.12170","repositories_listed":0,"syntology":null},{"url":null,"slug":"who-killed-lilly-kane-a-case-study-in","title":"Who killed Lilly Kane? A case study in applying knowledge graphs to crime fiction","date":"2020-11-24","arxiv_id":"2011.11804","repositories_listed":0,"syntology":null},{"url":null,"slug":"fact-checking-via-path-embedding-and","title":"Fact Checking via Path Embedding and Aggregation","date":"2020-11-16","arxiv_id":"2011.08028","repositories_listed":0,"syntology":null},{"url":null,"slug":"association-rules-enhanced-knowledge-graph","title":"Association Rules Enhanced Knowledge Graph Attention Network","date":"2020-11-14","arxiv_id":"2011.08431","repositories_listed":0,"syntology":null},{"url":null,"slug":"theoretical-knowledge-graph-reasoning-via","title":"Theoretical Rule-based Knowledge Graph Reasoning by Connectivity Dependency Discovery","date":"2020-11-12","arxiv_id":"2011.06174","repositories_listed":0,"syntology":null},{"url":null,"slug":"kompare-a-knowledge-graph-comparative","title":"KompaRe: A Knowledge Graph Comparative Reasoning System","date":"2020-11-06","arxiv_id":"2011.03189","repositories_listed":0,"syntology":null},{"url":null,"slug":"linking-openstreetmap-with-knowledge-graphs","title":"Linking OpenStreetMap with Knowledge Graphs -- Link Discovery for Schema-Agnostic Volunteered Geographic Information","date":"2020-11-06","arxiv_id":"2011.05841","repositories_listed":0,"syntology":null},{"url":null,"slug":"qmul-sds-at-sardistance2020-leveraging","title":"QMUL-SDS @ SardiStance: Leveraging Network Interactions to Boost Performance on Stance Detection using Knowledge Graphs","date":"2020-11-02","arxiv_id":"2011.01181","repositories_listed":0,"syntology":null},{"url":null,"slug":"bert-mk-integrating-graph-contextualized","title":"BERT-MK: Integrating Graph Contextualized Knowledge into Pre-trained Language Models","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"h2kgat-hierarchical-hyperbolic-knowledge","title":"H2KGAT: Hierarchical Hyperbolic Knowledge Graph Attention Network","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-physical-common-sense-as-knowledge","title":"Learning Physical Common Sense as Knowledge Graph Completion via BERT Data Augmentation and Constrained Tucker Factorization","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-sample-representation-learning-for-1","title":"Out-of-Sample Representation Learning for Knowledge Graphs","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"q-can-knowledge-graphs-be-used-to-answer","title":"Q. Can Knowledge Graphs be used to Answer Boolean Questions? A. It’s complicated!","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"recurrent-event-network-autoregressive","title":"Recurrent Event Network: Autoregressive Structure Inferenceover Temporal Knowledge Graphs","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"f56d88073a81cc1021a0ec58281660c1cb8c355d9883d5b0ca6dfd4707a9a02f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}