{"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/24","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":24,"pages_in_order":30,"rows_per_page":100,"rows":[2301,2400],"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/23","next":"/task/knowledge-graphs/papers/25","papers":[{"url":null,"slug":"improving-question-answering-over-knowledge","title":"Improving Question Answering over Knowledge Graphs Using Graph Summarization","date":"2022-03-25","arxiv_id":"2203.13570","repositories_listed":0,"syntology":null},{"url":null,"slug":"duality-induced-regularizer-for-semantic","title":"Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings","date":"2022-03-24","arxiv_id":"2203.12949","repositories_listed":0,"syntology":null},{"url":null,"slug":"bios-an-algorithmically-generated-biomedical","title":"BIOS: An Algorithmically Generated Biomedical Knowledge Graph","date":"2022-03-18","arxiv_id":"2203.09975","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhanced-temporal-knowledge-embeddings-with","title":"ECOLA: Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations","date":"2022-03-17","arxiv_id":"2203.09590","repositories_listed":0,"syntology":null},{"url":null,"slug":"personal-knowledge-graphs-use-cases-in-e","title":"Personal Knowledge Graphs: Use Cases in e-learning Platforms","date":"2022-03-16","arxiv_id":"2203.08507","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-theorem-provers-delineating-search","title":"Neural Theorem Provers Delineating Search Area Using RNN","date":"2022-03-14","arxiv_id":"2203.06985","repositories_listed":0,"syntology":null},{"url":null,"slug":"wcl-bbcd-a-contrastive-learning-and-knowledge","title":"WCL-BBCD: A Contrastive Learning and Knowledge Graph Approach to Named Entity Recognition","date":"2022-03-14","arxiv_id":"2203.06925","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-model-driven-negative-sampling","title":"LEMON: LanguagE ModeL for Negative Sampling of Knowledge Graph Embeddings","date":"2022-03-09","arxiv_id":"2203.04703","repositories_listed":0,"syntology":null},{"url":null,"slug":"module-module-embedding-for-knowledge-graphs","title":"ModulE: Module Embedding for Knowledge Graphs","date":"2022-03-09","arxiv_id":"2203.04702","repositories_listed":0,"syntology":null},{"url":null,"slug":"flurry-a-fast-framework-for-reproducible","title":"Flurry: a Fast Framework for Reproducible Multi-layered Provenance Graph Representation Learning","date":"2022-03-05","arxiv_id":"2203.02744","repositories_listed":0,"syntology":null},{"url":null,"slug":"scaling-r-gcn-training-with-graph","title":"Scaling R-GCN Training with Graph Summarization","date":"2022-03-05","arxiv_id":"2203.02622","repositories_listed":0,"syntology":null},{"url":null,"slug":"pattern-recognition-and-event-detection-on","title":"Pattern Recognition and Event Detection on IoT Data-streams","date":"2022-03-02","arxiv_id":"2203.01114","repositories_listed":0,"syntology":null},{"url":null,"slug":"pkgm-a-pre-trained-knowledge-graph-model-for","title":"PKGM: A Pre-trained Knowledge Graph Model for E-commerce Application","date":"2022-03-02","arxiv_id":"2203.00964","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-embodied-symbolic-concept","title":"Dual Embodied-Symbolic Concept Representations for Deep Learning","date":"2022-03-01","arxiv_id":"2203.00600","repositories_listed":0,"syntology":null},{"url":"/paper/improving-time-sensitivity-for-question","slug":"improving-time-sensitivity-for-question","title":"Improving Time Sensitivity for Question Answering over Temporal Knowledge Graphs","date":"2022-03-01","arxiv_id":"2203.00255","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-unstructured-text-to-causal-knowledge","title":"From Unstructured Text to Causal Knowledge Graphs: A Transformer-Based Approach","date":"2022-02-23","arxiv_id":"2202.11768","repositories_listed":0,"syntology":null},{"url":null,"slug":"rule-mining-over-knowledge-graphs-via","title":"Rule Mining over Knowledge Graphs via Reinforcement Learning","date":"2022-02-21","arxiv_id":"2202.10381","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixkg-mixing-for-harder-negative-samples-in","title":"MixKG: Mixing for harder negative samples in knowledge graph","date":"2022-02-19","arxiv_id":"2202.09606","repositories_listed":0,"syntology":null},{"url":null,"slug":"geometric-algebra-based-embeddings-for","title":"Geometric Algebra based Embeddings for Static and Temporal Knowledge Graph Completion","date":"2022-02-18","arxiv_id":"2202.09464","repositories_listed":0,"syntology":null},{"url":null,"slug":"unleashing-the-power-of-transformer-for","title":"Unleashing the Power of Transformer for Graphs","date":"2022-02-18","arxiv_id":"2202.10581","repositories_listed":0,"syntology":null},{"url":null,"slug":"discovering-fine-grained-semantics-in","title":"Discovering Fine-Grained Semantics in Knowledge Graph Relations","date":"2022-02-17","arxiv_id":"2202.08917","repositories_listed":0,"syntology":null},{"url":null,"slug":"mining-on-alzheimer-s-diseases-related","title":"Mining On Alzheimer's Diseases Related Knowledge Graph to Identity Potential AD-related Semantic Triples for Drug Repurposing","date":"2022-02-17","arxiv_id":"2202.08712","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-discover-medicines","title":"Learning to Discover Medicines","date":"2022-02-14","arxiv_id":"2202.07096","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-relationship-between-shy-and-warded","title":"On the Relationship between Shy and Warded Datalog+/-","date":"2022-02-13","arxiv_id":"2202.06285","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-knowledge-graph-construction-and","title":"Multi-Modal Knowledge Graph Construction and Application: A Survey","date":"2022-02-11","arxiv_id":"2202.05786","repositories_listed":0,"syntology":null},{"url":null,"slug":"complexity-of-arithmetic-in-warded-datalog","title":"Complexity of Arithmetic in Warded Datalog+-","date":"2022-02-10","arxiv_id":"2202.05086","repositories_listed":0,"syntology":null},{"url":"/paper/interht-knowledge-graph-embeddings-by","slug":"interht-knowledge-graph-embeddings-by","title":"InterHT: Knowledge Graph Embeddings by Interaction between Head and Tail Entities","date":"2022-02-10","arxiv_id":"2202.04897","repositories_listed":0,"syntology":null},{"url":null,"slug":"computing-rule-based-explanations-of-machine","title":"Computing Rule-Based Explanations of Machine Learning Classifiers using Knowledge Graphs","date":"2022-02-08","arxiv_id":"2202.03971","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-loosely-coupling-knowledge-graph","title":"Towards Loosely-Coupling Knowledge Graph Embeddings and Ontology-based Reasoning","date":"2022-02-07","arxiv_id":"2202.03173","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-a-theoretical-understanding-of-word","title":"Towards a Theoretical Understanding of Word and Relation Representation","date":"2022-02-01","arxiv_id":"2202.00486","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-representations-of-entities-and","title":"Learning Representations of Entities and Relations","date":"2022-01-31","arxiv_id":"2201.13073","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-visual-transfer-learning-using","title":"A Survey on Visual Transfer Learning using Knowledge Graphs","date":"2022-01-27","arxiv_id":"2201.11794","repositories_listed":0,"syntology":null},{"url":null,"slug":"ontology-enhanced-prompt-tuning-for-few-shot","title":"Ontology-enhanced Prompt-tuning for Few-shot Learning","date":"2022-01-27","arxiv_id":"2201.11332","repositories_listed":0,"syntology":null},{"url":null,"slug":"jointly-learning-knowledge-embedding-and","title":"Jointly Learning Knowledge Embedding and Neighborhood Consensus with Relational Knowledge Distillation for Entity Alignment","date":"2022-01-25","arxiv_id":"2201.11249","repositories_listed":0,"syntology":null},{"url":null,"slug":"taxonomy-enrichment-with-text-and-graph","title":"Taxonomy Enrichment with Text and Graph Vector Representations","date":"2022-01-21","arxiv_id":"2201.08598","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhanced-knowledge-graphs-using-typed","title":"Enhanced Knowledge Graphs Using Typed Entailment Graphs","date":"2022-01-20","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"do-kg-augmented-models-leverage-knowledge-as","title":"Do KG-augmented Models Leverage Knowledge as Humans Do?","date":"2022-01-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generalizable-neuro-symbolic-systems-for","title":"Generalizable Neuro-symbolic Systems for Commonsense Question Answering","date":"2022-01-17","arxiv_id":"2201.06230","repositories_listed":0,"syntology":null},{"url":null,"slug":"iclea-interactive-contrastive-learning-for-1","title":"Interactive Contrastive Learning for Self-supervised Entity Alignment","date":"2022-01-17","arxiv_id":"2201.06225","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-papers-iclr-2021","title":"Knowledge Graph Papers @ ICLR 2021","date":"2022-01-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"prior-knowledge-for-few-shot-learning","title":"Prior Knowledge for Few-shot Learning—Inductive Reasoning and Distribution Calibration","date":"2022-01-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-simple-but-powerful-graph-encoder-for","title":"A Simple But Powerful Graph Encoder for Temporal Knowledge Graph Completion","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/a-two-stage-approach-towards-generalization-1","slug":"a-two-stage-approach-towards-generalization-1","title":"A Two-Stage Approach towards Generalization in Knowledge Base Question Answering","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dangling-aware-entity-alignment-with-mixed","title":"Dangling-Aware Entity Alignment with Mixed High-Order Proximities","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"great-truths-are-always-simple-a-rather","title":"$Great~Truths~are ~Always ~Simple:$ A Rather Simple Knowledge Encoder for Enhancing the Commonsense Reasoning Capacity of Pre-Trained Models","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-relation-guided-type-sentence-1","title":"Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-conversational-recommendation-2","title":"Improving Conversational Recommendation Systems’ Quality with Context-Aware Item Meta-Information","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"jointlk-joint-reasoning-with-language-models-1","title":"JointLK: Joint Reasoning with Language Models and Knowledge Graphs for Commonsense Question Answering","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"kcd-knowledge-walks-and-textual-cues-enhanced","title":"KCD: Knowledge Walks and Textual Cues Enhanced Political Perspective Detection in News Media","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-based-template-machine-translation","title":"Knowledge Based Template Machine Translation In Low-Resource Setting","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-borrow-relation-representation","title":"Learning to Borrow– Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"modularized-transfer-learning-with-multiple","title":"Modularized Transfer Learning with Multiple Knowledge Graphs for Zero-shot Commonsense Reasoning","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"roof-bert-divide-understanding-labour-and-1","title":"Roof-BERT: Divide Understanding Labour and Join in Work","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"temporal-knowledge-graph-completion-a-survey","title":"Temporal Knowledge Graph Completion: A Survey","date":"2022-01-16","arxiv_id":"2201.08236","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-automatic-ontology-generation-framework","title":"An Automatic Ontology Generation Framework with An Organizational Perspective","date":"2022-01-15","arxiv_id":"2201.05910","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-a-reference-software-architecture-for","title":"Towards a Reference Software Architecture for Human-AI Teaming in Smart Manufacturing","date":"2022-01-13","arxiv_id":"2201.04876","repositories_listed":0,"syntology":null},{"url":null,"slug":"causalkg-causal-knowledge-graph","title":"CausalKG: Causal Knowledge Graph Explainability using interventional and counterfactual reasoning","date":"2022-01-06","arxiv_id":"2201.03647","repositories_listed":0,"syntology":null},{"url":"/paper/relationship-extraction-for-knowledge-graph","slug":"relationship-extraction-for-knowledge-graph","title":"Comparison of biomedical relationship extraction methods and models for knowledge graph creation","date":"2022-01-05","arxiv_id":"2201.01647","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-inference-approach-to-question-answering","title":"An Inference Approach To Question Answering Over Knowledge Graphs","date":"2021-12-21","arxiv_id":"2112.11070","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-object-detection-using-knowledge","title":"Contrastive Object Detection Using Knowledge Graph Embeddings","date":"2021-12-21","arxiv_id":"2112.11366","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-resource-learning-with-knowledge-graphs-a","title":"Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Survey","date":"2021-12-18","arxiv_id":"2112.10006","repositories_listed":0,"syntology":null},{"url":null,"slug":"kgboost-a-classification-based-knowledge-base","title":"KGBoost: A Classification-based Knowledge Base Completion Method with Negative Sampling","date":"2021-12-17","arxiv_id":"2112.09340","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-enhanced-recommender-system","title":"Knowledge graph enhanced recommender system","date":"2021-12-17","arxiv_id":"2112.09425","repositories_listed":0,"syntology":null},{"url":null,"slug":"link-intensive-alignment-for-incomplete","title":"Incomplete Knowledge Graph Alignment","date":"2021-12-17","arxiv_id":"2112.09266","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-embedding-in-e-commerce","title":"Knowledge Graph Embedding in E-commerce Applications: Attentive Reasoning, Explanations, and Transferable Rules","date":"2021-12-16","arxiv_id":"2112.08589","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-simple-but-powerful-graph-encoder-for-1","title":"A Simple But Powerful Graph Encoder for Temporal Knowledge Graph Completion","date":"2021-12-14","arxiv_id":"2112.07791","repositories_listed":0,"syntology":null},{"url":null,"slug":"roof-bert-divide-understanding-labour-and","title":"Roof-Transformer: Divided and Joined Understanding with Knowledge Enhancement","date":"2021-12-13","arxiv_id":"2112.06736","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-knowledge-graph-representation","title":"Improving Knowledge Graph Representation Learning by Structure Contextual Pre-training","date":"2021-12-08","arxiv_id":"2112.04087","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-select-the-next-reasonable","title":"Learning to Select the Next Reasonable Mention for Entity Linking","date":"2021-12-08","arxiv_id":"2112.04104","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-truelearn-using-semantic-knowledge","title":"Semantic TrueLearn: Using Semantic Knowledge Graphs in Recommendation Systems","date":"2021-12-08","arxiv_id":"2112.04368","repositories_listed":0,"syntology":null},{"url":null,"slug":"easy-semantification-of-bioassays","title":"Easy Semantification of Bioassays","date":"2021-11-30","arxiv_id":"2111.15182","repositories_listed":0,"syntology":null},{"url":null,"slug":"mdistmult-a-multiple-scoring-functions-model","title":"MDistMult: A Multiple Scoring Functions Model for Link Prediction on Antiviral Drugs Knowledge Graph","date":"2021-11-29","arxiv_id":"2111.14480","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-based-path-exploration","title":"Reinforcement Learning based Path Exploration for Sequential Explainable Recommendation","date":"2021-11-24","arxiv_id":"2111.12262","repositories_listed":0,"syntology":null},{"url":null,"slug":"triple-classification-for-scholarly-knowledge","title":"Triple Classification for Scholarly Knowledge Graph Completion","date":"2021-11-23","arxiv_id":"2111.11845","repositories_listed":0,"syntology":null},{"url":null,"slug":"walkingtime-dynamic-graph-embedding-using","title":"WalkingTime: Dynamic Graph Embedding Using Temporal-Topological Flows","date":"2021-11-22","arxiv_id":"2111.10928","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-biomedical-recommendations-via","title":"Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs","date":"2021-11-20","arxiv_id":"2111.10625","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-gnn-over-evolving-graphs-using","title":"Explaining GNN over Evolving Graphs using Information Flow","date":"2021-11-19","arxiv_id":"2111.10037","repositories_listed":0,"syntology":null},{"url":null,"slug":"alleviating-the-sparsity-of-open-knowledge","title":"Alleviating the Sparsity of Open Knowledge Graphs with Pretrained Contrastive Learning","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-investigation-of-commonsense","title":"An Empirical Investigation of Commonsense Self-Supervision with Knowledge Graphs","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"distilling-causal-metaknowledge-from-massive","title":"Distilling Causal Metaknowledge from Massive Knowledge Graph","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fair-comparison-of-knowledge-graphs-for","title":"Fair comparison of knowledge graphs for question answering","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-knowledge-graph-completion-with-data","title":"Few-Shot Knowledge Graph Completion with Data Fusion and Augmentation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"iclea-interactive-contrastive-learning-for","title":"ICLEA: Interactive Contrastive Learning for Self-supervised Entity Alignment","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-enhanced-embedding-improve-model","title":"Knowledge Enhanced Embedding: Improve Model Generalization Through Knowledge Graphs","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"language-model-guided-knowledge-subgraphs-for","title":"Language Model-Guided Knowledge Subgraphs for Question Answering","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-missing-relations-contrastive","title":"Learning from Missing Relations: Contrastive Learning with Commonsense Knowledge Graphs for Commonsense Inference","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-use-of-entity-embeddings-from-pre","title":"On the Use of Entity Embeddings from Pre-Trained Language Models for Knowledge Graph Completion","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-robust-knowledge-graph-embedding-via","title":"Towards Robust Knowledge Graph Embedding via Multi-task Reinforcement Learning","date":"2021-11-11","arxiv_id":"2111.06103","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-two-stage-approach-towards-generalization","title":"A Two-Stage Approach towards Generalization in Knowledge Base Question Answering","date":"2021-11-10","arxiv_id":"2111.05825","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-probit-tensor-factorization-model-for","title":"A Probit Tensor Factorization Model For Relational Learning","date":"2021-11-06","arxiv_id":"2111.03943","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditional-attention-networks-for-distilling","title":"Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation","date":"2021-11-03","arxiv_id":"2111.02100","repositories_listed":0,"syntology":null},{"url":null,"slug":"order-matters-matching-multiple-knowledge","title":"Order Matters: Matching Multiple Knowledge Graphs","date":"2021-11-03","arxiv_id":"2111.02239","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-semantic-filter-based-on-relations-for","title":"A Semantic Filter Based on Relations for Knowledge Graph Completion","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/crfr-improving-conversational-recommender","slug":"crfr-improving-conversational-recommender","title":"CRFR: Improving Conversational Recommender Systems via Flexible Fragments Reasoning on Knowledge Graphs","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"eventke-event-enhanced-knowledge-graph","title":"EventKE: Event-Enhanced Knowledge Graph Embedding","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hyperbolic-hierarchy-aware-knowledge-graph","title":"Hyperbolic Hierarchy-Aware Knowledge Graph Embedding for Link Prediction","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-transformers-and-knowledge-graphs","title":"Integrating Transformers and Knowledge Graphs for Twitter Stance Detection","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-representation-learning-with","title":"Knowledge Representation Learning with Contrastive Completion Coding","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-neural-ordinary-equations-for","title":"Learning Neural Ordinary Equations for Forecasting Future Links on Temporal Knowledge Graphs","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"low-resource-quadratic-forms-for-knowledge","title":"Low Resource Quadratic Forms for Knowledge Graph Embeddings","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"7aef154fd5b4d1438a137b422e8695186e6328d0ed65f352e33273c512059a3a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}