Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:43:04.173820Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2507.13411.
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 2026-08-06T16:43:04.173820Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-26T11:00:19.246229Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T08:49:41.740971Z
47 of 47 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 53095e84-3986-45e3-8827-899d8143518f · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Gemini: A Family of Highly Capable Multimodal Models
Reference 1
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Claude: An AI Assistant
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Aligning Knowledge Graphs and Language Models for Factual Accuracy URL: https://www.anthropic.com/product
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Knowledge-Augmented Language Model Verification
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Fine-Tuning Large Enter- prise Language Models via Ontological Reasoning
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Softening Ontological Rea- soning with Large Language Models
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Gett-qa: Graph embedding based t2t transformer for knowledge graph question answering
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Aligning Knowledge Graphs and Language Models for Factual Accuracy LLMs Will Always Hallucinate, and We Need to Live With This
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Observation a76bce3a-4f04-41c5-820e-0f88806379cc · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Besold et al., eds
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Translating embeddings for modeling multi-relational data
Reference 10
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Observation b5772bac-b562-4337-85fc-0b849b32b970 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Language Models are Few-Shot Learners
Reference 11
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Sparks of Artificial General Intelligence: Early experiments with GPT-4
Reference 12
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Observation b27404ab-2dfa-4828-801c-3b436de2376c · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Knowledge Graph Embedding: A Survey from the Perspective of Representation Spaces
Reference 13
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Observation a6995607-6d1f-4c5c-9410-c1de42a5bcc1 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy REANO: Optimising Retrieval-Augmented Reader Models through Knowledge Graph Generation
Reference 14
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Observation 0e0ef871-faa4-4ed9-889e-82bdb3e5c99c · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Mitigating large language model hallucinations via autonomous knowledge graph-based retrofitting
Reference 15
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Distributed Company Control in Company Shareholding Graphs
Reference 16
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Knowledgenavigator: Leveraging large language models for enhanced reasoning over knowledge graph
Reference 17
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Observation 90cd5b4d-e72a-4f02-95b8-e49a30b97829 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy A Survey on Knowledge Graphs: Representation, Acquisition, and Applications
Reference 18
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Survey of hallucination in natural lan- guage generation
Reference 19
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Observation 1fa39611-77fd-419d-be14-b360e5faf2dc · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Mistral 7B
Reference 20
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Observation d2da48c9-e840-443b-a07a-f88c5e2d2783 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Efficient Knowledge Infusion via KG-LLM Alignment
Reference 21
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Observation 98dc1232-ecbf-48b3-bc42-4a097e5183f0 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning
Reference 22
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Visual instruction tuning
Reference 23
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Aligning Knowledge Graphs and Language Models for Factual Accuracy ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models
Reference 24
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Aligning Knowledge Graphs and Language Models for Factual Accuracy KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation
Reference 25
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Observation 7b30cf25-51e9-4e5e-8fab-9c599d08b591 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Dataset: YAGO3-10 (Yet Another Great Ontology 3-10)
Reference 26
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Aligning Knowledge Graphs and Language Models for Factual Accuracy When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories
Reference 27
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Observation 4b3ed5f1-5ef7-428a-939b-de7c26005ac9 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy GPT-4 Technical Report
Reference 28
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Observation db92d39a-a9fc-48b2-9dcc-ede12b5753f1 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Unifying large language models and knowledge graphs: A roadmap
Reference 29
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Relation-aware language-graph transformer for question answering
Reference 30
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Observation d8d4458a-5d90-4c8d-a99e-834d0bb22abf · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback
Reference 31
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Knowledge Enhanced Contextual Word Representations
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering
Reference 33
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Observation 7957e8bf-2ee5-4c86-adf7-7e2570252790 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy JointLK: Joint Reasoning with Language Models and Knowledge Graphs for Commonsense Question Answering
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Aligning Knowledge Graphs and Language Models for Factual Accuracy RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
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Aligning Knowledge Graphs and Language Models for Factual Accuracy KG-adapter: Enabling knowledge graph integration in large language models through parameter-efficient fine-tuning
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Aligning Knowledge Graphs and Language Models for Factual Accuracy LLaMA: Open and Efficient Foundation Language Models
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Knowledge graph embedding: A sur- vey of approaches and applications
Reference 38
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Observation 84ddb62f-db2f-4454-9072-1d18a4e01215 · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy KEPLER: A unified model for knowledge embedding and pre-trained language repre- sentation
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Resolving Knowledge Conflicts in Large Language Models
Reference 40
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Thinking with Knowledge Graphs: Enhancing LLM Reasoning Through Structured Data
Reference 41
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Aligning Knowledge Graphs and Language Models for Factual Accuracy QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
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Aligning Knowledge Graphs and Language Models for Factual Accuracy TinyLlama: An Open-Source Small Language Model
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Aligning Knowledge Graphs and Language Models for Factual Accuracy ERNIE: Enhanced Language Representation with Informative Entities
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Fine-tuning Large Language Models for Domain-specific Machine Translation
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Aligning Knowledge Graphs and Language Models for Factual Accuracy Judging llm-as-a-judge with mt-bench and chatbot arena
Reference 46
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Observation eef126e1-b972-421f-b97a-643d1b5ba44c · outbound
Aligning Knowledge Graphs and Language Models for Factual Accuracy GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
Reference 47
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Observation 2b515138-29ae-4835-b4c4-4f6d42a1bb33 · inbound
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