[HTML][HTML] A survey on complex factual question answering
Answering complex factual questions has drawn a lot of attention. Researchers leverage
various data sources to support complex QA, such as unstructured texts, structured …
various data sources to support complex QA, such as unstructured texts, structured …
Can ChatGPT replace traditional KBQA models? An in-depth analysis of the question answering performance of the GPT LLM family
ChatGPT is a powerful large language model (LLM) that covers knowledge resources such
as Wikipedia and supports natural language question answering using its own knowledge …
as Wikipedia and supports natural language question answering using its own knowledge …
Language models as controlled natural language semantic parsers for knowledge graph question answering
We propose the use of controlled natural language as a target for knowledge graph question
answering (KGQA) semantic parsing via language models as opposed to using formal query …
answering (KGQA) semantic parsing via language models as opposed to using formal query …
Text-to-SQL error correction with language models of code
Despite recent progress in text-to-SQL parsing, current semantic parsers are still not
accurate enough for practical use. In this paper, we investigate how to build automatic text-to …
accurate enough for practical use. In this paper, we investigate how to build automatic text-to …
Exploring Equation as a Better Intermediate Meaning Representation for Numerical Reasoning of Large Language Models
Numerical reasoning is a vital capability for natural language processing models to
understand and process numerical information in real-world scenarios. Most current …
understand and process numerical information in real-world scenarios. Most current …
Self-supervised BGP-graph reasoning enhanced complex KBQA via SPARQL generation
Abstract Knowledge base question answering aims to answer complex questions from large-
scale knowledge bases. Although existing generative language models that translate …
scale knowledge bases. Although existing generative language models that translate …
Probing structured semantics understanding and generation of language models via question answering
Recent advancement in the capabilities of large language models (LLMs) has triggered a
new surge in LLMs' evaluation. Most recent evaluation works tends to evaluate the …
new surge in LLMs' evaluation. Most recent evaluation works tends to evaluate the …
VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering
We present Visual Knowledge oriented Programming platform (VisKoP), a knowledge base
question answering (KBQA) system that integrates human into the loop to edit and debug …
question answering (KBQA) system that integrates human into the loop to edit and debug …
Dynamic multi teacher knowledge distillation for semantic parsing in KBQA
Abstract Knowledge base question answering (KBQA) is an important task of extracting
answers from a knowledge base by analyzing natural language questions. Semantic …
answers from a knowledge base by analyzing natural language questions. Semantic …
Triple alignment-enhanced complex question answering over knowledge bases
D Wang, S Zhou, J Huang, X Ni - Neurocomputing, 2024 - Elsevier
Program induction is a crucial paradigm for complex question answering over knowledge
bases. In the existing learning framework, the predicted program is required to strictly align …
bases. In the existing learning framework, the predicted program is required to strictly align …