Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:48:08.762913Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2506.09566.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:48:08.762913Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
69 of 69 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 89d469be-920c-4464-851f-1a24f6b61035 · outbound
From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Llama3.1:A405b-parameteropen-sourcelanguagemodel.https: //github.com/facebookresearch/llama, 2024
Reference 1
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Mixtral 8x22b: Sparse mixture-of-experts model with 141b parameters.https://github.com/mistralai/Mixtral, 2024
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Language model guided knowledge graph embeddings.IEEE Access, 10:76008–76020, 2022
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies SciBERT: A pretrained language model for scientific text
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Courville, and Pascal Vincent
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Unresolved cited work
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Unresolved cited work
Reference 9
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies PairRE: Knowl- edge graph embeddings via paired relation vectors
Reference 10
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies SAC-KG: Exploiting large language models as skilled automatic construc- torsfordomainknowledgegraph
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Augmenting multimodal llms with self-reflective tokens for knowledge-based visual question answering, 2025
Reference 12
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Command r: A retrieval-augmented open source language model
Reference 13
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Command r+: Enhanced version for large-scale tasks.https: //github.com/cohere-ai/command-r-plus, 2024
Reference 14
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Gemma: Lightweight llms in 2b and 7b sizes.https: //github.com/google-research/gemma, 2024
Reference 15
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Reference 16
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies BERT: Pre-training of deep bidirectional transformers for language under- standing
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Core techniques of question answering systems over knowledge bases: A survey
Reference 18
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Knowledge vault: a web-scale approach to probabilistic knowledge fusion
Reference 19
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Enrich- ing contextualized language model from knowledge graph for biomedical information extraction.Briefings in bioinformatics, 22(3):bbaa110, 2021
Reference 20
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Comprehensive analysis of knowledge graph embedding techniques benchmarked on link prediction.Electronics, 11(23):3866, 2022
Reference 21
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies A survey on knowledge graph-based recommender sys- tems.IEEE Transactions on Knowledge and Data Engineering, 34(8):3549– 3568, 2022
Reference 22
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, and Antoine Zimmermann.Knowledge Graphs
Reference 23
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Knowledge graphs.ACM Computing Surveys (Csur), 54(4):1–37, 2021
Reference 24
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Observation c227afbe-c72f-46c6-9c93-802756c95552 · outbound
From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies A survey of knowledge-enhanced pre-trained language models.IEEE Trans- actions on Knowledge and Data Engineering, 36:1413–1430, 2023
Reference 25
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Can llms be good graph judger for knowledge graph construction?, 2025
Reference 26
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Improving knowledge graph em- bedding using locally and globally attentive relation paths
Reference 27
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Carte: pretraining and transfer for tabular learning
Reference 28
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Knowledge graph informed fake news classification via heterogeneous representation ensembles.Neurocomputing, 496:208–226, 2022
Reference 29
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Jamba: A production-grade hybrid llm.https://github.com/ ai21labs/Jamba, 2024
Reference 30
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Decoding on Graphs: Faithful and Sound Reasoning on Knowledge Graphs through Generation of Well-Formed Chains
Reference 31
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies TransE-MTP: A new representation learn- ing method for knowledge graph embedding with multi-translation princi- ples and TransE.Electronics, 13(16):3171, 2024
Reference 32
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Dual Reason- ing: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering
Reference 33
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies K-BERT: enabling language representation with knowl- edge graph
Reference 34
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation
Reference 35
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs
Reference 36
Source-reported events for the cited work
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Phi-3 medium: A 14b-parameter language model.https:// github.com/microsoft/phi, 2024
Reference 37
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Corrado, and Jeffrey Dean
Reference 38
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Dbrx: An open-source mixture-of-experts language model.https://github.com/databricks/DBRX, 2024
Reference 39
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Nemotron-4: A 340b-parameter open source language model
Reference 40
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Unresolved cited work
Reference 41
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Unifying Large Language Models and Knowledge Graphs: A Roadmap
Reference 42
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Observation d72bcec4-ccb7-4d67-ad38-720ebf224c4e · outbound
From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Unifying large language models and knowledge graphs: A roadmap
Reference 43
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Observation 82fd05fa-5969-4cac-aa15-2d64e53bb16d · outbound
From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Knowl- edge graphs: Opportunities and challenges.Artificial Intelligence Review, 56(11):13071–13102, 2023
Reference 44
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies GloVe: Global vectors for word representation
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Reference 46
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Reference 49
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Reference 50
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Reference 51
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Synthesis Lectures on Data, Semantics, and Knowledge
Reference 52
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Reference 53
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Conceptnet 5.5: An open multilingual graph of general knowledge
Reference 54
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Ernie: Enhanced representation through knowledge integration
Reference 55
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies LaMDA: Language Models for Dialog Applications
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Reference 57
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Gomez, Lukasz Kaiser, and Illia Polosukhin
Reference 58
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs
Reference 59
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies A survey on knowledge graph embeddings for link prediction.Symmetry, 13(3):485, 2021
Reference 60
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Mindmap: Prompting large language models with knowledge graphs for graph-of- thoughtreasoning
Reference 61
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Fact-aware generation in large language models.https://example.org/yang2024factaware, 2024
Reference 62
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Toward better drug discovery with knowledge graph.Current opinion in structural biology, 72:114–126, 2022
Reference 63
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Kg-enhanced reasoning in large language models
Reference 64
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Making Large Language Models Perform Better in Knowledge Graph Completion
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies A Survey of Large Language Models
Reference 67
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From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies A survey of knowl- edge graph construction using machine learning.Computer Modeling in Engineering & Sciences, 139(1):225–257, 2024
Reference 68
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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7d2d828b-e0b5-4fe4-940e-eeee0b4a6c6f · outbound
From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities
Reference 69
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