Graph Question Answering
25 papers with code • 1 benchmarks • 1 datasets
GQA
Most implemented papers
$μ\text{KG}$: A Library for Multi-source Knowledge Graph Embeddings and Applications
nju-websoft/mukg
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It is useful for a thorough comparison and analysis of various embedding models and tasks.
ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs
Our method, termed ReaRev, introduces a new way to KGQA reasoning with respect to both instruction decoding and execution.
Learning Action-Effect Dynamics for Hypothetical Vision-Language Reasoning Task
shailaja183/arl
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'Actions' play a vital role in how humans interact with the world.
An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering
Large-scale pre-trained language models (PLMs) such as BERT have recently achieved great success and become a milestone in natural language processing (NLP).
GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question Answering
debayan/gett-qa
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To further improve the results, we instruct the model to produce a truncated version of the KG embedding for each entity.
The Role of Output Vocabulary in T2T LMs for SPARQL Semantic Parsing
debayan/sparql-vocab-substitution
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In this work, we analyse the role of output vocabulary for text-to-text (T2T) models on the task of SPARQL semantic parsing.
Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering
wuyike2000/retrieve-rewrite-answer
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To this end, we propose an answer-sensitive KG-to-Text approach that can transform KG knowledge into well-textualized statements most informative for KGQA.
Spider4SPARQL: A Complex Benchmark for Evaluating Knowledge Graph Question Answering Systems
With the recent spike in the number and availability of Large Language Models (LLMs), it has become increasingly important to provide large and realistic benchmarks for evaluating Knowledge Graph Question Answering (KGQA) systems.
NuTrea: Neural Tree Search for Context-guided Multi-hop KGQA
mlvlab/nutrea
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NeurIPS 2023
Multi-hop Knowledge Graph Question Answering (KGQA) is a task that involves retrieving nodes from a knowledge graph (KG) to answer natural language questions.
NLQxform: A Language Model-based Question to SPARQL Transformer
In recent years, scholarly data has grown dramatically in terms of both scale and complexity.
