{"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/17","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":17,"pages_in_order":30,"rows_per_page":100,"rows":[1601,1700],"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/16","next":"/task/knowledge-graphs/papers/18","papers":[{"url":null,"slug":"posets-and-bounded-probabilities-for","title":"Posets and Bounded Probabilities for Discovering Order-inducing Features in Event Knowledge Graphs","date":"2024-10-08","arxiv_id":"2410.06065","repositories_listed":0,"syntology":null},{"url":null,"slug":"representing-web-applications-as-knowledge","title":"Representing Web Applications As Knowledge Graphs","date":"2024-10-06","arxiv_id":"2410.17258","repositories_listed":0,"syntology":null},{"url":"/paper/neuro-symbolic-entity-alignment-via","slug":"neuro-symbolic-entity-alignment-via","title":"Neuro-Symbolic Entity Alignment via Variational Inference","date":"2024-10-05","arxiv_id":"2410.04153","repositories_listed":0,"syntology":{"n":14,"n_ran":6,"n_constructed":4,"n_ran_checked":6,"n_instrument":0,"n_unverified":8,"n_honours":2,"n_violates":0,"n_no_contract":4,"n_pointer_only":14,"phrase":"6 ran (of which 4 constructed an object rather than computing a result; 6 with no instrument failure: 2 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/neuro-symbolic-entity-alignment-via#ran","syntology_url":"https://syntology.ai/paper/2410.04153","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.04153"}},"official":null}},{"url":null,"slug":"domain-specific-retrieval-augmented","title":"Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorization","date":"2024-10-03","arxiv_id":"2410.02721","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-guided-rl-for-interpretable-feature","title":"Semantic-Guided RL for Interpretable Feature Engineering","date":"2024-10-03","arxiv_id":"2410.02519","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-kg-vldb-24-workshop-summary","title":"LLM+KG@VLDB'24 Workshop Summary","date":"2024-10-02","arxiv_id":"2410.01978","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-natural-language-to-sql-review-of-llm","title":"From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems","date":"2024-10-01","arxiv_id":"2410.01066","repositories_listed":0,"syntology":null},{"url":null,"slug":"customized-information-and-domain-centric","title":"Customized Information and Domain-centric Knowledge Graph Construction with Large Language Models","date":"2024-09-30","arxiv_id":"2409.20010","repositories_listed":0,"syntology":null},{"url":null,"slug":"gundam-aligning-large-language-models-with","title":"GUNDAM: Aligning Large Language Models with Graph Understanding","date":"2024-09-30","arxiv_id":"2409.20053","repositories_listed":0,"syntology":null},{"url":null,"slug":"rehearsing-answers-to-probable-questions-with","title":"Rehearsing Answers to Probable Questions with Perspective-Taking","date":"2024-09-27","arxiv_id":"2409.18678","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-structured-data-retrieval-with","title":"Enhancing Structured-Data Retrieval with GraphRAG: Soccer Data Case Study","date":"2024-09-26","arxiv_id":"2409.17580","repositories_listed":0,"syntology":null},{"url":null,"slug":"kipps-knowledge-infusion-in-privacy","title":"KIPPS: Knowledge infusion in Privacy Preserving Synthetic Data Generation","date":"2024-09-25","arxiv_id":"2409.17315","repositories_listed":0,"syntology":null},{"url":null,"slug":"sac-kg-exploiting-large-language-models-as","title":"SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graphs","date":"2024-09-22","arxiv_id":"2410.02811","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-assistants-for-spaceflight-procedures","title":"AI Assistants for Spaceflight Procedures: Combining Generative Pre-Trained Transformer and Retrieval-Augmented Generation on Knowledge Graphs With Augmented Reality Cues","date":"2024-09-21","arxiv_id":"2409.14206","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-automated-patent-workflows-ai","title":"Towards Automated Patent Workflows: AI-Orchestrated Multi-Agent Framework for Intellectual Property Management and Analysis","date":"2024-09-21","arxiv_id":"2409.19006","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-knowledge-graphs-and-llms-to","title":"Leveraging Knowledge Graphs and LLMs to Support and Monitor Legislative Systems","date":"2024-09-20","arxiv_id":"2409.13252","repositories_listed":0,"syntology":null},{"url":null,"slug":"procedure-model-for-building-knowledge-graphs","title":"Procedure Model for Building Knowledge Graphs for Industry Applications","date":"2024-09-20","arxiv_id":"2409.13425","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowformer-revisiting-transformers-for","title":"KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning","date":"2024-09-19","arxiv_id":"2409.12865","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-based-domain-oriented-data","title":"Enhancing Unsupervised Sentence Embeddings via Knowledge-Driven Data Augmentation and Gaussian-Decayed Contrastive Learning","date":"2024-09-19","arxiv_id":"2409.12887","repositories_listed":0,"syntology":null},{"url":null,"slug":"geometric-relational-embeddings","title":"Geometric Relational Embeddings","date":"2024-09-18","arxiv_id":"2409.15369","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-knowledge-enhanced-disease-diagnosis-method","title":"A Knowledge-Enhanced Disease Diagnosis Method Based on Prompt Learning and BERT Integration","date":"2024-09-16","arxiv_id":"2409.10403","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-der-a-named-entity-recognition-method","title":"LLM-DER:A Named Entity Recognition Method Based on Large Language Models for Chinese Coal Chemical Domain","date":"2024-09-16","arxiv_id":"2409.10077","repositories_listed":0,"syntology":null},{"url":null,"slug":"mgsa-multi-granularity-graph-structure","title":"MGSA: Multi-Granularity Graph Structure Attention for Knowledge Graph-to-Text Generation","date":"2024-09-16","arxiv_id":"2409.10294","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-rag-approach-for-generating-competency","title":"A RAG Approach for Generating Competency Questions in Ontology Engineering","date":"2024-09-13","arxiv_id":"2409.08820","repositories_listed":0,"syntology":null},{"url":null,"slug":"contri-e-ve-context-retrieve-for-scholarly","title":"Contri(e)ve: Context + Retrieve for Scholarly Question Answering","date":"2024-09-13","arxiv_id":"2409.09010","repositories_listed":0,"syntology":null},{"url":null,"slug":"winning-solution-for-meta-kdd-cup-24","title":"Winning Solution For Meta KDD Cup' 24","date":"2024-09-13","arxiv_id":"2410.00005","repositories_listed":0,"syntology":null},{"url":null,"slug":"influence-of-backdoor-paths-on-causal-link","title":"Influence of Backdoor Paths on Causal Link Prediction","date":"2024-09-12","arxiv_id":"2410.14680","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-interoperability-on-blockchain-by","title":"Semantic Interoperability on Blockchain by Generating Smart Contracts Based on Knowledge Graphs","date":"2024-09-11","arxiv_id":"2409.12171","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-tuning-and-prompt-engineering-with","title":"Fine-tuning and Prompt Engineering with Cognitive Knowledge Graphs for Scholarly Knowledge Organization","date":"2024-09-10","arxiv_id":"2409.06433","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-llms-and-knowledge-graphs-to-reduce","title":"Combining LLMs and Knowledge Graphs to Reduce Hallucinations in Question Answering","date":"2024-09-06","arxiv_id":"2409.04181","repositories_listed":0,"syntology":null},{"url":null,"slug":"neurosymbolic-methods-for-dynamic-knowledge","title":"Neurosymbolic Methods for Dynamic Knowledge Graphs","date":"2024-09-06","arxiv_id":"2409.04572","repositories_listed":0,"syntology":null},{"url":null,"slug":"rx-strategist-prescription-verification-using","title":"Rx Strategist: Prescription Verification using LLM Agents System","date":"2024-09-05","arxiv_id":"2409.03440","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-fkg-in-a-knowledge-graph-for-indian","title":"Building FKG.in: a Knowledge Graph for Indian Food","date":"2024-09-01","arxiv_id":"2409.00830","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-based-multi-hop-question-answering-with","title":"LLM-Based Multi-Hop Question Answering with Knowledge Graph Integration in Evolving Environments","date":"2024-08-28","arxiv_id":"2408.15903","repositories_listed":0,"syntology":null},{"url":null,"slug":"cl4kge-a-curriculum-learning-method-for","title":"CL4KGE: A Curriculum Learning Method for Knowledge Graph Embedding","date":"2024-08-27","arxiv_id":"2408.14840","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-the-predictive-features-of-person","title":"Evaluating the Predictive Features of Person-Centric Knowledge Graph Embeddings: Unfolding Ablation Studies","date":"2024-08-27","arxiv_id":"2408.15294","repositories_listed":0,"syntology":null},{"url":null,"slug":"tripletoile-extraction-of-knowledge-from","title":"Triplètoile: Extraction of Knowledge from Microblogging Text","date":"2024-08-27","arxiv_id":"2408.14908","repositories_listed":0,"syntology":null},{"url":null,"slug":"kgprune-a-web-application-to-extract","title":"KGPrune: a Web Application to Extract Subgraphs of Interest from Wikidata with Analogical Pruning","date":"2024-08-26","arxiv_id":"2408.14658","repositories_listed":0,"syntology":null},{"url":null,"slug":"drugagent-explainable-drug-repurposing-agent","title":"DrugAgent: Multi-Agent Large Language Model-Based Reasoning for Drug-Target Interaction Prediction","date":"2024-08-23","arxiv_id":"2408.13378","repositories_listed":0,"syntology":null},{"url":null,"slug":"hardware-acceleration-for-knowledge-graph","title":"Hardware Acceleration for Knowledge Graph Processing: Challenges & Recent Developments","date":"2024-08-22","arxiv_id":"2408.12173","repositories_listed":0,"syntology":null},{"url":null,"slug":"meddit-a-knowledge-controlled-diffusion","title":"MedDiT: A Knowledge-Controlled Diffusion Transformer Framework for Dynamic Medical Image Generation in Virtual Simulated Patient","date":"2024-08-22","arxiv_id":"2408.12236","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-open-knowledge-graph-based-approach-for","title":"An Open Knowledge Graph-Based Approach for Mapping Concepts and Requirements between the EU AI Act and International Standards","date":"2024-08-21","arxiv_id":"2408.11925","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-large-language-models-capabilities","title":"GS-KGC: A Generative Subgraph-based Framework for Knowledge Graph Completion with Large Language Models","date":"2024-08-20","arxiv_id":"2408.10819","repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-the-graph-reasoning-ability-of","title":"Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path","date":"2024-08-18","arxiv_id":"2408.09529","repositories_listed":0,"syntology":null},{"url":null,"slug":"asgm-kg-unveiling-alluvial-gold-mining","title":"ASGM-KG: Unveiling Alluvial Gold Mining Through Knowledge Graphs","date":"2024-08-16","arxiv_id":"2408.08972","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-relational-triple-extraction-with","title":"Multimodal Relational Triple Extraction with Query-based Entity Object Transformer","date":"2024-08-16","arxiv_id":"2408.08709","repositories_listed":0,"syntology":null},{"url":null,"slug":"cegrl-tkgr-a-causal-enhanced-graph","title":"CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Temporal Knowledge Graph Reasoning","date":"2024-08-15","arxiv_id":"2408.07911","repositories_listed":0,"syntology":null},{"url":null,"slug":"conformalized-answer-set-prediction-for","title":"Conformalized Answer Set Prediction for Knowledge Graph Embedding","date":"2024-08-15","arxiv_id":"2408.08248","repositories_listed":0,"syntology":null},{"url":null,"slug":"kgv-integrating-large-language-models-with","title":"KGV: Integrating Large Language Models with Knowledge Graphs for Cyber Threat Intelligence Credibility Assessment","date":"2024-08-15","arxiv_id":"2408.08088","repositories_listed":0,"syntology":null},{"url":null,"slug":"predictive-multiplicity-of-knowledge-graph","title":"Predictive Multiplicity of Knowledge Graph Embeddings in Link Prediction","date":"2024-08-15","arxiv_id":"2408.08226","repositories_listed":0,"syntology":null},{"url":null,"slug":"qirk-question-answering-via-intermediate","title":"QirK: Question Answering via Intermediate Representation on Knowledge Graphs","date":"2024-08-14","arxiv_id":"2408.07494","repositories_listed":0,"syntology":null},{"url":null,"slug":"weknow-rag-an-adaptive-approach-for-retrieval","title":"WeKnow-RAG: An Adaptive Approach for Retrieval-Augmented Generation Integrating Web Search and Knowledge Graphs","date":"2024-08-14","arxiv_id":"2408.07611","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-and-frugal-text-graph-transformers-are","title":"Fast-and-Frugal Text-Graph Transformers are Effective Link Predictors","date":"2024-08-13","arxiv_id":"2408.06778","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-gene-function-prediction-challenge-large","title":"The gene function prediction challenge: large language models and knowledge graphs to the rescue","date":"2024-08-13","arxiv_id":"2408.07222","repositories_listed":0,"syntology":null},{"url":null,"slug":"unlock-the-power-of-frozen-llms-in-knowledge","title":"Bridging LLMs and KGs without Fine-Tuning: Intermediate Probing Meets Subgraph-Aware Entity Descriptions","date":"2024-08-13","arxiv_id":"2408.06787","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-methodological-report-on-anomaly-detection","title":"A Methodological Report on Anomaly Detection on Dynamic Knowledge Graphs","date":"2024-08-12","arxiv_id":"2408.06121","repositories_listed":0,"syntology":null},{"url":null,"slug":"convkgyarn-spinning-configurable-and-scalable","title":"ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA datasets with Large Language Models","date":"2024-08-12","arxiv_id":"2408.05948","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-dimensional-federated-knowledge-graph","title":"Low-Dimensional Federated Knowledge Graph Embedding via Knowledge Distillation","date":"2024-08-11","arxiv_id":"2408.05748","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybridrag-integrating-knowledge-graphs-and","title":"HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction","date":"2024-08-09","arxiv_id":"2408.04948","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-03079","title":"Enhancing Complex Causality Extraction via Improved Subtask Interaction and Knowledge Fusion","date":"2024-08-06","arxiv_id":"2408.03079","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-03166","title":"CADRL: Category-aware Dual-agent Reinforcement Learning for Explainable Recommendations over Knowledge Graphs","date":"2024-08-06","arxiv_id":"2408.03166","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-02707","title":"SnapE -- Training Snapshot Ensembles of Link Prediction Models","date":"2024-08-05","arxiv_id":"2408.02707","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-supply-chain-visibility-with","title":"Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models","date":"2024-08-05","arxiv_id":"2408.07705","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-01679","title":"MMPKUBase: A Comprehensive and High-quality Chinese Multi-modal Knowledge Graph","date":"2024-08-03","arxiv_id":"2408.01679","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-01784","title":"Graph Stochastic Neural Process for Inductive Few-shot Knowledge Graph Completion","date":"2024-08-03","arxiv_id":"2408.01784","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-01154","title":"DERA: Dense Entity Retrieval for Entity Alignment in Knowledge Graphs","date":"2024-08-02","arxiv_id":"2408.01154","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-00662","title":"Aligning Multiple Knowledge Graphs in a Single Pass","date":"2024-08-01","arxiv_id":"2408.00662","repositories_listed":0,"syntology":null},{"url":null,"slug":"2407-21276","title":"Multi-Level Querying using A Knowledge Pyramid","date":"2024-07-31","arxiv_id":"2407.21276","repositories_listed":0,"syntology":null},{"url":null,"slug":"2407-21483","title":"eSPARQL: Representing and Reconciling Agnostic and Atheistic Beliefs in RDF-star Knowledge Graphs","date":"2024-07-31","arxiv_id":"2407.21483","repositories_listed":0,"syntology":null},{"url":null,"slug":"clr-fact-evaluating-the-complex-logical","title":"CLR-Fact: Evaluating the Complex Logical Reasoning Capability of Large Language Models over Factual Knowledge","date":"2024-07-30","arxiv_id":"2407.20564","repositories_listed":0,"syntology":null},{"url":null,"slug":"topictag-automatic-annotation-of-nmf-topic","title":"TopicTag: Automatic Annotation of NMF Topic Models Using Chain of Thought and Prompt Tuning with LLMs","date":"2024-07-29","arxiv_id":"2407.19616","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-if-red-can-talk-dynamic-dialogue","title":"What if Red Can Talk? Dynamic Dialogue Generation Using Large Language Models","date":"2024-07-29","arxiv_id":"2407.20382","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-communication-enhanced-by-knowledge","title":"Semantic Communication Enhanced by Knowledge Graph Representation Learning","date":"2024-07-27","arxiv_id":"2407.19338","repositories_listed":0,"syntology":null},{"url":null,"slug":"look-globally-and-reason-two-stage-path","title":"Look Globally and Reason: Two-stage Path Reasoning over Sparse Knowledge Graphs","date":"2024-07-26","arxiv_id":"2407.18556","repositories_listed":0,"syntology":null},{"url":null,"slug":"synergizing-knowledge-graphs-with-large","title":"Synergizing Knowledge Graphs with Large Language Models: A Comprehensive Review and Future Prospects","date":"2024-07-26","arxiv_id":"2407.18470","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-gpt-4-to-guide-causal-machine-learning","title":"Using GPT-4 to guide causal machine learning","date":"2024-07-26","arxiv_id":"2407.18607","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-entity-alignment-towards-complete","title":"Beyond Entity Alignment: Towards Complete Knowledge Graph Alignment via Entity-Relation Synergy","date":"2024-07-25","arxiv_id":"2407.17745","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-ad-hoc-graph-node-vector-embedding","title":"An Ad-hoc graph node vector embedding algorithm for general knowledge graphs using Kinetica-Graph","date":"2024-07-22","arxiv_id":"2407.15906","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-data-limited-graph-neural-networks","title":"Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language Models","date":"2024-07-19","arxiv_id":"2407.13989","repositories_listed":0,"syntology":null},{"url":null,"slug":"hecix-integrating-knowledge-graphs-and-large","title":"HeCiX: Integrating Knowledge Graphs and Large Language Models for Biomedical Research","date":"2024-07-19","arxiv_id":"2407.14030","repositories_listed":0,"syntology":null},{"url":null,"slug":"pragyan-connecting-the-dots-in-tweets","title":"PRAGyan -- Connecting the Dots in Tweets","date":"2024-07-18","arxiv_id":"2407.13909","repositories_listed":0,"syntology":null},{"url":null,"slug":"mindful-rag-a-study-of-points-of-failure-in","title":"Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation","date":"2024-07-16","arxiv_id":"2407.12216","repositories_listed":0,"syntology":null},{"url":null,"slug":"converging-paradigms-the-synergy-of-symbolic","title":"Converging Paradigms: The Synergy of Symbolic and Connectionist AI in LLM-Empowered Autonomous Agents","date":"2024-07-11","arxiv_id":"2407.08516","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-graph-neural-networks-for-node","title":"Explaining Graph Neural Networks for Node Similarity on Graphs","date":"2024-07-10","arxiv_id":"2407.07639","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-knowledge-graphs-and-large-language","title":"Combining Knowledge Graphs and Large Language Models","date":"2024-07-09","arxiv_id":"2407.06564","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-probabilistic-logic-learning-for","title":"Neural Probabilistic Logic Learning for Knowledge Graph Reasoning","date":"2024-07-04","arxiv_id":"2407.03704","repositories_listed":0,"syntology":null},{"url":null,"slug":"croppable-knowledge-graph-embedding","title":"Croppable Knowledge Graph Embedding","date":"2024-07-03","arxiv_id":"2407.02779","repositories_listed":0,"syntology":null},{"url":null,"slug":"sf-gnn-self-filter-for-message-lossless","title":"SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network","date":"2024-07-03","arxiv_id":"2407.02762","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-knowledge-graph-learning-in","title":"Automated Knowledge Graph Learning in Industrial Processes","date":"2024-07-02","arxiv_id":"2407.02106","repositories_listed":0,"syntology":null},{"url":null,"slug":"ensuring-responsible-sourcing-of-large","title":"LLMs Plagiarize: Ensuring Responsible Sourcing of Large Language Model Training Data Through Knowledge Graph Comparison","date":"2024-07-02","arxiv_id":"2407.02659","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-few-shot-learning-for-knowledge-graph","title":"Dynamic Few-Shot Learning for Knowledge Graph Question Answering","date":"2024-07-01","arxiv_id":"2407.01409","repositories_listed":0,"syntology":null},{"url":null,"slug":"actionable-cyber-threat-intelligence-using","title":"Actionable Cyber Threat Intelligence using Knowledge Graphs and Large Language Models","date":"2024-06-30","arxiv_id":"2407.02528","repositories_listed":0,"syntology":null},{"url":null,"slug":"chain-of-knowledge-integrating-knowledge","title":"Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs","date":"2024-06-30","arxiv_id":"2407.00653","repositories_listed":0,"syntology":null},{"url":null,"slug":"sanskrit-knowledge-based-systems-annotation","title":"Sanskrit Knowledge-based Systems: Annotation and Computational Tools","date":"2024-06-26","arxiv_id":"2406.18276","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-consistency-image-generation-pcig-a","title":"Prompt-Consistency Image Generation (PCIG): A Unified Framework Integrating LLMs, Knowledge Graphs, and Controllable Diffusion Models","date":"2024-06-24","arxiv_id":"2406.16333","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-powered-explanations-unraveling","title":"LLM-Powered Explanations: Unraveling Recommendations Through Subgraph Reasoning","date":"2024-06-22","arxiv_id":"2406.15859","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-of-feature-selection-strategies","title":"A review of feature selection strategies utilizing graph data structures and knowledge graphs","date":"2024-06-21","arxiv_id":"2406.14864","repositories_listed":0,"syntology":null},{"url":null,"slug":"pathformer-recursive-path-query-encoding-for","title":"Pathformer: Recursive Path Query Encoding for Complex Logical Query Answering","date":"2024-06-21","arxiv_id":"2406.14880","repositories_listed":0,"syntology":null},{"url":null,"slug":"relation-extraction-with-fine-tuned-large","title":"Relation Extraction with Fine-Tuned Large Language Models in Retrieval Augmented Generation Frameworks","date":"2024-06-20","arxiv_id":"2406.14745","repositories_listed":0,"syntology":null},{"url":null,"slug":"communication-efficient-federated-knowledge","title":"Communication-Efficient Federated Knowledge Graph Embedding with Entity-Wise Top-K Sparsification","date":"2024-06-19","arxiv_id":"2406.13225","repositories_listed":0,"syntology":null}],"record_sha256":"f0010ba5e9677effd8a4f31d51e365dde36a19c5f0d40e9960afde7949c7b5a0","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}