SOTAVerified

Graph Question Answering

Papers

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Showing 26–50 of 78 papers

TitleStatusHype
Integrating Multi-Head Convolutional Encoders with Cross-Attention for Improved SPARQL Query Translation—0
MST5 -- Multilingual Question Answering over Knowledge GraphsCode0
Dynamic Few-Shot Learning for Knowledge Graph Question Answering—0
BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical ScienceCode0
TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language modelsCode2
Temporal Knowledge Graph Question Answering: A Survey—0
LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-AnsweringCode1
UniOQA: A Unified Framework for Knowledge Graph Question Answering with Large Language Models—0
GNN-RAG: Graph Neural Retrieval for Large Language Model ReasoningCode3
FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering—0
KG-RAG: Bridging the Gap Between Knowledge and Creativity—0
Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question AnsweringCode2
Self-Improvement Programming for Temporal Knowledge Graph Question Answering—0
CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail KnowledgeCode1
Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering—0
Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models—0
Question Answering Over Spatio-Temporal Knowledge Graph—0
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question AnsweringCode4
GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended TasksCode2
Joint Multi-Facts Reasoning Network For Complex Temporal Question Answering Over Knowledge Graph—0
Leveraging LLMs in Scholarly Knowledge Graph Question AnsweringCode0
NLQxform: A Language Model-based Question to SPARQL TransformerCode0
NuTrea: Neural Tree Search for Context-guided Multi-hop KGQACode1
PSYCHIC: A Neuro-Symbolic Framework for Knowledge Graph Question-Answering GroundingCode0
Answer Candidate Type Selection: Text-to-Text Language Model for Closed Book Question Answering Meets Knowledge Graphs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GraphVQAAccuracy96.3—Unverified
2GCNAccuracy85.7—Unverified