{"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/21","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":21,"pages_in_order":30,"rows_per_page":100,"rows":[2001,2100],"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/20","next":"/task/knowledge-graphs/papers/22","papers":[{"url":null,"slug":"knowledge-enhanced-neuro-symbolic-ai-for","title":"Knowledge-enhanced Neuro-Symbolic AI for Cybersecurity and Privacy","date":"2023-07-25","arxiv_id":"2308.02031","repositories_listed":0,"syntology":null},{"url":null,"slug":"word-sense-disambiguation-as-a-game-of","title":"Word Sense Disambiguation as a Game of Neurosymbolic Darts","date":"2023-07-25","arxiv_id":"2307.16663","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-knowledge-graph-completion-using","title":"Fast Knowledge Graph Completion using Graphics Processing Units","date":"2023-07-22","arxiv_id":"2307.12059","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-knowledge-graphs-for-zero-shot","title":"Leveraging Knowledge Graphs for Zero-Shot Object-agnostic State Classification","date":"2023-07-22","arxiv_id":"2307.12179","repositories_listed":0,"syntology":null},{"url":null,"slug":"named-entity-resolution-in-personal-knowledge","title":"Named Entity Resolution in Personal Knowledge Graphs","date":"2023-07-22","arxiv_id":"2307.12173","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmark-datasets-for-biomedical-knowledge","title":"Benchmark datasets for biomedical knowledge graphs with negative statements","date":"2023-07-21","arxiv_id":"2307.11719","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-constraint-based-recommender-system-via-rdf","title":"A Constraint-based Recommender System via RDF Knowledge Graphs","date":"2023-07-20","arxiv_id":"2307.10702","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-personalized-recommender-system-based-on","title":"A Personalized Recommender System Based-on Knowledge Graph Embeddings","date":"2023-07-20","arxiv_id":"2307.10680","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-ontologically-grounded-and-language","title":"Towards Ontologically Grounded and Language-Agnostic Knowledge Graphs","date":"2023-07-20","arxiv_id":"2307.11206","repositories_listed":0,"syntology":null},{"url":null,"slug":"neurosymbolic-ai-for-reasoning-on-biomedical","title":"Neurosymbolic AI for Reasoning on Biomedical Knowledge Graphs","date":"2023-07-17","arxiv_id":"2307.08411","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-inference-for-data-efficient","title":"Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review","date":"2023-07-16","arxiv_id":"2307.08024","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-enhanced-intelligent-tutoring","title":"Knowledge Graph Enhanced Intelligent Tutoring System Based on Exercise Representativeness and Informativeness","date":"2023-07-15","arxiv_id":"2307.15076","repositories_listed":0,"syntology":null},{"url":null,"slug":"logkg-log-failure-diagnosis-through-knowledge","title":"LogKG: Log Failure Diagnosis Through Knowledge Graph","date":"2023-07-11","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"separate-and-aggregate-a-transformer-based","title":"Separate-and-Aggregate: A Transformer-based Patch Refinement Model for Knowledge Graph Completion","date":"2023-07-11","arxiv_id":"2307.05627","repositories_listed":0,"syntology":null},{"url":null,"slug":"digital-twins-for-patient-care-via-knowledge","title":"Digital Twins for Patient Care via Knowledge Graphs and Closed-Form Continuous-Time Liquid Neural Networks","date":"2023-07-08","arxiv_id":"2307.04772","repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-guided-multi-modal-pre-trained","title":"Structure Guided Multi-modal Pre-trained Transformer for Knowledge Graph Reasoning","date":"2023-07-06","arxiv_id":"2307.03591","repositories_listed":0,"syntology":null},{"url":null,"slug":"verifai-verified-generative-ai","title":"VerifAI: Verified Generative AI","date":"2023-07-06","arxiv_id":"2307.02796","repositories_listed":0,"syntology":null},{"url":null,"slug":"combating-confirmation-bias-a-unified-pseudo","title":"Combating Confirmation Bias: A Unified Pseudo-Labeling Framework for Entity Alignment","date":"2023-07-05","arxiv_id":"2307.02075","repositories_listed":0,"syntology":null},{"url":null,"slug":"power-up-what-can-generative-models-do-for","title":"Power-up! What Can Generative Models Do for Human Computation Workflows?","date":"2023-07-05","arxiv_id":"2307.02243","repositories_listed":0,"syntology":null},{"url":null,"slug":"concept2box-joint-geometric-embeddings-for","title":"Concept2Box: Joint Geometric Embeddings for Learning Two-View Knowledge Graphs","date":"2023-07-04","arxiv_id":"2307.01933","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-for-nlg-in-the-context-of","title":"Knowledge Graph for NLG in the context of conversational agents","date":"2023-07-04","arxiv_id":"2307.01548","repositories_listed":0,"syntology":null},{"url":null,"slug":"iterative-zero-shot-llm-prompting-for","title":"Iterative Zero-Shot LLM Prompting for Knowledge Graph Construction","date":"2023-07-03","arxiv_id":"2307.01128","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-pretraining-for-biomedical-term","title":"Hierarchical Pretraining for Biomedical Term Embeddings","date":"2023-07-01","arxiv_id":"2307.00266","repositories_listed":0,"syntology":null},{"url":null,"slug":"ierl-interpretable-ensemble-representation","title":"IERL: Interpretable Ensemble Representation Learning -- Combining CrowdSourced Knowledge and Distributed Semantic Representations","date":"2023-06-24","arxiv_id":"2306.13865","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-infused-self-attention-transformers","title":"Knowledge-Infused Self Attention Transformers","date":"2023-06-23","arxiv_id":"2306.13501","repositories_listed":0,"syntology":null},{"url":null,"slug":"chatgpt-is-not-enough-enhancing-large","title":"Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling","date":"2023-06-20","arxiv_id":"2306.11489","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-tuning-large-enterprise-language-models","title":"Fine-tuning Large Enterprise Language Models via Ontological Reasoning","date":"2023-06-19","arxiv_id":"2306.10723","repositories_listed":0,"syntology":null},{"url":null,"slug":"temporal-data-meets-llm-explainable-financial","title":"Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting","date":"2023-06-19","arxiv_id":"2306.11025","repositories_listed":0,"syntology":null},{"url":null,"slug":"tourist-attractions-recommendation-based-on","title":"Att-KGCN: Tourist Attractions Recommendation System by using Attention mechanism and Knowledge Graph Convolution Network","date":"2023-06-19","arxiv_id":"2306.10946","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-as-i-can-not-as-i-get-topology-aware-multi","title":"Do as I can, not as I get","date":"2023-06-17","arxiv_id":"2306.10345","repositories_listed":0,"syntology":null},{"url":null,"slug":"dsmtgcn-a-direction-sensitive-multi-task","title":"DsMtGCN: A Direction-sensitive Multi-task framework for Knowledge Graph Completion","date":"2023-06-17","arxiv_id":"2306.10290","repositories_listed":0,"syntology":null},{"url":null,"slug":"query2gmm-learning-representation-with","title":"Query2GMM: Learning Representation with Gaussian Mixture Model for Reasoning over Knowledge Graphs","date":"2023-06-17","arxiv_id":"2306.10367","repositories_listed":0,"syntology":null},{"url":null,"slug":"recap-kg-mining-knowledge-graphs-from-raw-gp","title":"RECAP-KG: Mining Knowledge Graphs from Raw GP Notes for Remote COVID-19 Assessment in Primary Care","date":"2023-06-17","arxiv_id":"2306.17175","repositories_listed":0,"syntology":null},{"url":null,"slug":"snowman-a-million-scale-chinese-commonsense","title":"Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model","date":"2023-06-17","arxiv_id":"2306.10241","repositories_listed":0,"syntology":null},{"url":null,"slug":"august-an-automatic-generation-understudy-for","title":"AUGUST: an Automatic Generation Understudy for Synthesizing Conversational Recommendation Datasets","date":"2023-06-16","arxiv_id":"2306.09631","repositories_listed":0,"syntology":null},{"url":null,"slug":"recognizing-unseen-objects-via-multimodal","title":"Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation","date":"2023-06-14","arxiv_id":"2306.08487","repositories_listed":0,"syntology":null},{"url":null,"slug":"unifying-large-language-models-and-knowledge","title":"Unifying Large Language Models and Knowledge Graphs: A Roadmap","date":"2023-06-14","arxiv_id":"2306.08302","repositories_listed":0,"syntology":null},{"url":null,"slug":"contextual-dictionary-lookup-for-knowledge","title":"Contextual Dictionary Lookup for Knowledge Graph Completion","date":"2023-06-13","arxiv_id":"2306.07719","repositories_listed":0,"syntology":null},{"url":null,"slug":"noisy-positive-unlabeled-learning-with-self","title":"Noisy Positive-Unlabeled Learning with Self-Training for Speculative Knowledge Graph Reasoning","date":"2023-06-13","arxiv_id":"2306.07512","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-practical-entity-linking-system-for-tables","title":"A Practical Entity Linking System for Tables in Scientific Literature","date":"2023-06-12","arxiv_id":"2306.10044","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-knowledge-driven-critiquing-with","title":"Bayesian Knowledge-driven Critiquing with Indirect Evidence","date":"2023-06-09","arxiv_id":"2306.05636","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-knowledge-enhancement-for-zero","title":"Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application","date":"2023-06-09","arxiv_id":"2306.06302","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-knowledge-graphs-for-healthcare","title":"A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises","date":"2023-06-07","arxiv_id":"2306.04802","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-knowledge-graph-embeddings-to","title":"Leveraging Knowledge Graph Embeddings to Enhance Contextual Representations for Relation Extraction","date":"2023-06-07","arxiv_id":"2306.04203","repositories_listed":0,"syntology":null},{"url":null,"slug":"skg-a-versatile-information-retrieval-and","title":"SKG: A Versatile Information Retrieval and Analysis Framework for Academic Papers with Semantic Knowledge Graphs","date":"2023-06-07","arxiv_id":"2306.04758","repositories_listed":0,"syntology":null},{"url":null,"slug":"triggering-multi-hop-reasoning-for-question","title":"Triggering Multi-Hop Reasoning for Question Answering in Language Models using Soft Prompts and Random Walks","date":"2023-06-06","arxiv_id":"2306.04009","repositories_listed":0,"syntology":null},{"url":null,"slug":"construction-d-un-systeme-de-recommandation","title":"Construction d'un système de recommandation basé sur des contraintes via des graphes de connaissances","date":"2023-06-05","arxiv_id":"2306.03247","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-to-kg-alignment-comparing-current","title":"Text-To-KG Alignment: Comparing Current Methods on Classification Tasks","date":"2023-06-05","arxiv_id":"2306.02871","repositories_listed":0,"syntology":null},{"url":null,"slug":"gode-integrating-biochemical-knowledge-graph","title":"Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations","date":"2023-06-02","arxiv_id":"2306.01631","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-reasoning-for-question-answering-with","title":"Graph Reasoning for Question Answering with Triplet Retrieval","date":"2023-05-30","arxiv_id":"2305.18742","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-representation-learning-via-epistemic","title":"Epistemic Graph: A Plug-And-Play Module For Hybrid Representation Learning","date":"2023-05-30","arxiv_id":"2305.18731","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-augmented-language-models-for","title":"Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation","date":"2023-05-30","arxiv_id":"2305.18846","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-categorical-representation-language-and","title":"A Categorical Representation Language and Computational System for Knowledge-Based Planning","date":"2023-05-26","arxiv_id":"2305.17208","repositories_listed":0,"syntology":null},{"url":null,"slug":"buca-a-binary-classification-approach-to","title":"BUCA: A Binary Classification Approach to Unsupervised Commonsense Question Answering","date":"2023-05-25","arxiv_id":"2305.15932","repositories_listed":0,"syntology":null},{"url":null,"slug":"collective-knowledge-graph-completion-with","title":"Collective Knowledge Graph Completion with Mutual Knowledge Distillation","date":"2023-05-25","arxiv_id":"2305.15895","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-relentless-benchmark-for-modelling-graded","title":"A RelEntLess Benchmark for Modelling Graded Relations between Named Entities","date":"2023-05-24","arxiv_id":"2305.15002","repositories_listed":0,"syntology":null},{"url":null,"slug":"conversational-recommendation-as-retrieval-a","title":"Conversational Recommendation as Retrieval: A Simple, Strong Baseline","date":"2023-05-23","arxiv_id":"2305.13725","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graphs-querying","title":"Knowledge Graphs Querying","date":"2023-05-23","arxiv_id":"2305.14485","repositories_listed":0,"syntology":null},{"url":null,"slug":"message-intercommunication-for-inductive","title":"Message Intercommunication for Inductive Relation Reasoning","date":"2023-05-23","arxiv_id":"2305.14074","repositories_listed":0,"syntology":null},{"url":null,"slug":"graphcare-enhancing-healthcare-predictions","title":"GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs","date":"2023-05-22","arxiv_id":"2305.12788","repositories_listed":0,"syntology":null},{"url":null,"slug":"nesy4vrd-a-multifaceted-resource-for","title":"NeSy4VRD: A Multifaceted Resource for Neurosymbolic AI Research using Knowledge Graphs in Visual Relationship Detection","date":"2023-05-22","arxiv_id":"2305.13258","repositories_listed":0,"syntology":null},{"url":null,"slug":"direct-fact-retrieval-from-knowledge-graphs","title":"Direct Fact Retrieval from Knowledge Graphs without Entity Linking","date":"2023-05-21","arxiv_id":"2305.12416","repositories_listed":0,"syntology":null},{"url":null,"slug":"prodigy-enabling-in-context-learning-over","title":"PRODIGY: Enabling In-context Learning Over Graphs","date":"2023-05-21","arxiv_id":"2305.12600","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-completion-models-are-few","title":"Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs","date":"2023-05-17","arxiv_id":"2305.09858","repositories_listed":0,"syntology":null},{"url":null,"slug":"constructing-and-interpreting-causal","title":"Constructing and Interpreting Causal Knowledge Graphs from News","date":"2023-05-16","arxiv_id":"2305.09359","repositories_listed":0,"syntology":null},{"url":null,"slug":"growing-and-serving-large-open-domain","title":"Growing and Serving Large Open-domain Knowledge Graphs","date":"2023-05-16","arxiv_id":"2305.09464","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-in-context-learning-capabilities-of","title":"Exploring In-Context Learning Capabilities of Foundation Models for Generating Knowledge Graphs from Text","date":"2023-05-15","arxiv_id":"2305.08804","repositories_listed":0,"syntology":null},{"url":null,"slug":"neustip-a-novel-neuro-symbolic-model-for-link","title":"NeuSTIP: A Novel Neuro-Symbolic Model for Link and Time Prediction in Temporal Knowledge Graphs","date":"2023-05-15","arxiv_id":"2305.11301","repositories_listed":0,"syntology":null},{"url":null,"slug":"answering-complex-questions-over-text-by","title":"HPE:Answering Complex Questions over Text by Hybrid Question Parsing and Execution","date":"2023-05-12","arxiv_id":"2305.07789","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-interoperable-electronic-health","title":"Building Interoperable Electronic Health Records as Purpose-Driven Knowledge Graphs","date":"2023-05-10","arxiv_id":"2305.06088","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-link-prediction-on-n-ary-facts","title":"Few-shot Link Prediction on N-ary Facts","date":"2023-05-10","arxiv_id":"2305.06104","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-hop-commonsense-knowledge-injection","title":"Multi-hop Commonsense Knowledge Injection Framework for Zero-Shot Commonsense Question Answering","date":"2023-05-10","arxiv_id":"2305.05936","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-knowledge-graph-construction-using","title":"Enhancing Knowledge Graph Construction Using Large Language Models","date":"2023-05-08","arxiv_id":"2305.04676","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-enhanced-agents-for-interactive","title":"Knowledge-enhanced Agents for Interactive Text Games","date":"2023-05-08","arxiv_id":"2305.05091","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-guided-semantic-evaluation-of","title":"Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust","date":"2023-05-08","arxiv_id":"2305.04989","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-source-education-knowledge-graph","title":"Multi-source Education Knowledge Graph Construction and Fusion for College Curricula","date":"2023-05-08","arxiv_id":"2305.04567","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-the-automated-construction-of","title":"Toward the Automated Construction of Probabilistic Knowledge Graphs for the Maritime Domain","date":"2023-05-04","arxiv_id":"2305.02471","repositories_listed":0,"syntology":null},{"url":null,"slug":"ripple-knowledge-graph-convolutional-networks","title":"Ripple Knowledge Graph Convolutional Networks For Recommendation Systems","date":"2023-05-02","arxiv_id":"2305.01147","repositories_listed":0,"syntology":null},{"url":null,"slug":"constructing-a-knowledge-graph-from-textual","title":"Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database","date":"2023-04-30","arxiv_id":"2305.00382","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhance-enhanced-entity-and-relation","title":"EnhancE：Enhanced Entity and Relation Embedding for Knowledge Hypergraph Link Prediction","date":"2023-04-30","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieval-based-knowledge-augmented-vision","title":"Retrieval-based Knowledge Augmented Vision Language Pre-training","date":"2023-04-27","arxiv_id":"2304.13923","repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-diagrammatic-queries-in-viziquer","title":"Visual Diagrammatic Queries in ViziQuer: Overview and Implementation","date":"2023-04-27","arxiv_id":"2304.14825","repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-diagram-recognition-in-financial","title":"Structure Diagram Recognition in Financial Announcements","date":"2023-04-26","arxiv_id":"2304.13240","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-spoken-information-queries-for","title":"Modeling Spoken Information Queries for Virtual Assistants: Open Problems, Challenges and Opportunities","date":"2023-04-25","arxiv_id":"2304.13149","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-semantic-and-structural-representation","title":"Joint Semantic and Structural Representation Learning for Enhancing User Preference Modelling","date":"2023-04-24","arxiv_id":"2304.12083","repositories_listed":0,"syntology":null},{"url":null,"slug":"bert-based-clinical-knowledge-extraction-for","title":"BERT Based Clinical Knowledge Extraction for Biomedical Knowledge Graph Construction and Analysis","date":"2023-04-21","arxiv_id":"2304.10996","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantics-ontology-and-explanation","title":"Semantics, Ontology and Explanation","date":"2023-04-21","arxiv_id":"2304.11124","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-potential-of-artificial-intelligence","title":"On the Potential of Artificial Intelligence Chatbots for Data Exploration of Federated Bioinformatics Knowledge Graphs","date":"2023-04-20","arxiv_id":"2304.10427","repositories_listed":0,"syntology":null},{"url":null,"slug":"sarf-aliasing-relation-assisted-self","title":"SARF: Aliasing Relation Assisted Self-Supervised Learning for Few-shot Relation Reasoning","date":"2023-04-20","arxiv_id":"2304.10297","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-ecosystem-for-personal-knowledge-graphs-a","title":"An Ecosystem for Personal Knowledge Graphs: A Survey and Research Roadmap","date":"2023-04-19","arxiv_id":"2304.09572","repositories_listed":0,"syntology":null},{"url":null,"slug":"empowering-ai-drug-discovery-with-explicit","title":"Towards Unified AI Drug Discovery with Multiple Knowledge Modalities","date":"2023-04-17","arxiv_id":"2305.01523","repositories_listed":0,"syntology":null},{"url":null,"slug":"agi-for-agriculture","title":"AGI for Agriculture","date":"2023-04-12","arxiv_id":"2304.06136","repositories_listed":0,"syntology":null},{"url":null,"slug":"hiprompt-few-shot-biomedical-knowledge-fusion","title":"HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting","date":"2023-04-12","arxiv_id":"2304.05973","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-multiple-rdf-knowledge-graphs-for","title":"Using Multiple RDF Knowledge Graphs for Enriching ChatGPT Responses","date":"2023-04-12","arxiv_id":"2304.05774","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-structured-sentences-with-time","title":"Incorporating Structured Sentences with Time-enhanced BERT for Fully-inductive Temporal Relation Prediction","date":"2023-04-10","arxiv_id":"2304.04717","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-graph-structure-information-for","title":"Investigating Graph Structure Information for Entity Alignment with Dangling Cases","date":"2023-04-10","arxiv_id":"2304.04718","repositories_listed":0,"syntology":null},{"url":null,"slug":"dream-adaptive-reinforcement-learning-based","title":"DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning","date":"2023-04-08","arxiv_id":"2304.03984","repositories_listed":0,"syntology":null},{"url":null,"slug":"attribute-consistent-knowledge-graph","title":"Attribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignment","date":"2023-04-04","arxiv_id":"2304.01563","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-throughput-vector-similarity-search-in","title":"High-Throughput Vector Similarity Search in Knowledge Graphs","date":"2023-04-04","arxiv_id":"2304.01926","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-clinical-evidence-recommendation","title":"Enhancing Clinical Evidence Recommendation with Multi-Channel Heterogeneous Learning on Evidence Graphs","date":"2023-04-03","arxiv_id":"2304.01242","repositories_listed":0,"syntology":null}],"record_sha256":"f1f82e0482c4851bcb1b29a6f56f853ba58d9253ab4c9192e2adc0a614015c40","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}