This work forms the task of Information-Needs-Guided VKG Enrichment (IN-VKGE), and proposes an iterative framework that leverages large language models to assess whether information needs can be supported using SPARQL execution feedback and generate ontology and mapping enrichment proposals.
Lin Ren, Guohui Xiao, Guilin Qi et al.· Proceedings of the Thirty-Fi...· 0 citations
This paper studies the VKG-QA task, which enables users to interact with the VKGs through a natural language (NL) interface by translating their questions into SPARQL queries, and pro-poses NaVQA (Navigation-based VKG Question Answering), a framework leveraging Large Language Models.
Guohui Xiao, Haohan Xue, Lin Ren et al.· Proceedings of the Thirty-Fi...· 0 citations
EvoThink is proposed, a framework that reduces redundant verification and encourages the exploration of new reasoning paths that not only substantially reduces inference-time token usage but also improves the reasoning capability of LRMs.
Xinbang Dai, Zheyu Xin, Hui-Kang Hu et al.· arXiv.org· 0 citations
Compilable Academic Document Parsing (CADP) is proposed, a paradigm that reconstructs a full page as contextual \LaTeX{} plus executable Python, so that structure-preserving elements and executable chart representations can be reconstructed, recompiled, and directly verified against the source page.
Rihui Jin, Jun Wang, Chen Zhu et al.· 0 citations
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