[HTML][HTML] A survey on complex factual question answering

L Zhang, J Zhang, X Ke, H Li, X Huang, Z Shao, S Cao… - AI Open, 2023 - Elsevier
Answering complex factual questions has drawn a lot of attention. Researchers leverage
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

Y Tan, D Min, Y Li, W Li, N Hu, Y Chen, G Qi - International Semantic Web …, 2023 - Springer
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 …

Language models as controlled natural language semantic parsers for knowledge graph question answering

J Lehmann, P Gattogi, D Bhandiwad, S Ferré… - ECAI 2023, 2023 - ebooks.iospress.nl
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 …

Text-to-SQL error correction with language models of code

Z Chen, S Chen, M White, R Mooney, A Payani… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

Exploring Equation as a Better Intermediate Meaning Representation for Numerical Reasoning of Large Language Models

D Wang, L Dou, W Zhang, J Zeng, W Che - Proceedings of the AAAI …, 2024 - ojs.aaai.org
Numerical reasoning is a vital capability for natural language processing models to
understand and process numerical information in real-world scenarios. Most current …

Self-supervised BGP-graph reasoning enhanced complex KBQA via SPARQL generation

F Gao, Y Yang, P Gao, M Gu, S Zhao, Y Chen… - Information Processing …, 2024 - Elsevier
Abstract Knowledge base question answering aims to answer complex questions from large-
scale knowledge bases. Although existing generative language models that translate …

Probing structured semantics understanding and generation of language models via question answering

J Liu, S Cao, J Shi, T Zhang, L Hou, J Li - arXiv preprint arXiv:2401.05777, 2024 - arxiv.org
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 …

VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering

Z Yao, Y Chen, X Lv, S Cao, A Xin, J Yu, H Jin… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

Dynamic multi teacher knowledge distillation for semantic parsing in KBQA

A Zou, J Zou, S Cao, J Zhang, J Liu, J Wan… - Expert Systems with …, 2025 - Elsevier
Abstract Knowledge base question answering (KBQA) is an important task of extracting
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 …