Knowledge Graphs
959 papers with code • 3 benchmarks • 41 datasets
Benchmarks
These leaderboards are used to track progress in Knowledge Graphs
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Libraries
Use these libraries to find Knowledge Graphs models and implementationsDatasets
ConceptNet
FB15k
ATOMIC
CORD-19
ReDial
Semantic Scholar
MetaQA
DBP15K
ComplexWebQuestions
Jericho
Subtasks
Latest papers with no code
Graph Machine Learning in the Era of Large Language Models (LLMs)
Meanwhile, graphs, especially knowledge graphs, are rich in reliable factual knowledge, which can be utilized to enhance the reasoning capabilities of LLMs and potentially alleviate their limitations such as hallucinations and the lack of explainability.
Context-Enhanced Language Models for Generating Multi-Paper Citations
This research underscores the potential of harnessing LLMs for citation generation, opening a compelling avenue for exploring the intricate connections between scientific documents.
Reinforcement Learning Approach for Integrating Compressed Contexts into Knowledge Graphs
The widespread use of knowledge graphs in various fields has brought about a challenge in effectively integrating and updating information within them.
P-NAL: an Effective and Interpretable Entity Alignment Method
In this paper, we introduce P-NAL, an entity alignment method that captures two types of logical inference paths with Non-Axiomatic Logic (NAL).
EnriCo: Enriched Representation and Globally Constrained Inference for Entity and Relation Extraction
Joint entity and relation extraction plays a pivotal role in various applications, notably in the construction of knowledge graphs.
TC-OCR: TableCraft OCR for Efficient Detection & Recognition of Table Structure & Content
Our proposed approach achieves an IOU of 0. 96 and an OCR Accuracy of 78%, showcasing a remarkable improvement of approximately 25% in the OCR Accuracy compared to the previous Table Transformer approach.
German Tourism Knowledge Graph
Tourism is one of the most critical sectors of the global economy.
Automatic Knowledge Graph Construction for Judicial Cases
Building on these results, we detail the automatic construction process of case knowledge graphs for judicial cases, enabling the assembly of knowledge graphs for hundreds of thousands of judgments.
KG-CTG: Citation Generation through Knowledge Graph-guided Large Language Models
Citation Text Generation (CTG) is a task in natural language processing (NLP) that aims to produce text that accurately cites or references a cited document within a source document.
Progressive Knowledge Graph Completion
In this paper, we investigate three crucial processes relevant to real-world construction scenarios: (a) the verification process, which arises from the necessity and limitations of human verifiers; (b) the mining process, which identifies the most promising candidates for verification; and (c) the training process, which harnesses verified data for subsequent utilization; in order to achieve a transition toward more realistic challenges.
