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A survey on complex question answering over knowledge base: Recent advances and challenges
Question Answering (QA) over Knowledge Base (KB) aims to automatically answer natural
language questions via well-structured relation information between entities stored in …
language questions via well-structured relation information between entities stored in …
A survey on complex knowledge base question answering: Methods, challenges and solutions
Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Recently, a large number of studies focus on semantically or syntactically …
base (KB). Recently, a large number of studies focus on semantically or syntactically …
Subgraph retrieval enhanced model for multi-hop knowledge base question answering
Recent works on knowledge base question answering (KBQA) retrieve subgraphs for easier
reasoning. A desired subgraph is crucial as a small one may exclude the answer but a large …
reasoning. A desired subgraph is crucial as a small one may exclude the answer but a large …
Reinforced cross-modal alignment for radiology report generation
Medical images are widely used in clinical decision-making, where writing radiology reports
is a potential application that can be enhanced by automatic solutions to alleviate …
is a potential application that can be enhanced by automatic solutions to alleviate …
Complex knowledge base question answering: A survey
Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Early studies mainly focused on answering simple questions over KBs and …
base (KB). Early studies mainly focused on answering simple questions over KBs and …
Transfernet: An effective and transparent framework for multi-hop question answering over relation graph
Multi-hop Question Answering (QA) is a challenging task because it requires precise
reasoning with entity relations at every step towards the answer. The relations can be …
reasoning with entity relations at every step towards the answer. The relations can be …
KG-GPT: A general framework for reasoning on knowledge graphs using large language models
While large language models (LLMs) have made considerable advancements in
understanding and generating unstructured text, their application in structured data remains …
understanding and generating unstructured text, their application in structured data remains …
Leveraging abstract meaning representation for knowledge base question answering
Knowledge base question answering (KBQA) is an important task in Natural Language
Processing. Existing approaches face significant challenges including complex question …
Processing. Existing approaches face significant challenges including complex question …
Improving embedded knowledge graph multi-hop question answering by introducing relational chain reasoning
Abstract Knowledge Graph Question Answering (KGQA) aims to answer user-questions from
a knowledge graph (KG) by identifying the reasoning relations between topic entity and …
a knowledge graph (KG) by identifying the reasoning relations between topic entity and …
Tempoqr: temporal question reasoning over knowledge graphs
Abstract Knowledge Graph Question Answering (KGQA) involves retrieving facts from a
Knowledge Graph (KG) using natural language queries. A KG is a curated set of facts …
Knowledge Graph (KG) using natural language queries. A KG is a curated set of facts …