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Kai-Feng Jin

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Preprint Oct 2026

DIGEST: Discovery-Guided LLM Tuning for Symbolic Regression

Symbolic regression (SR) seeks to discover mathematical expressions directly from data, without requiring task-specific scientific descriptions. Despite tremendous progress in both conventional search-based methods and recent LLM-based methods, two critical limitations largely remain. First (Limited Generation Flexibil...

Kai-Feng Jin, Rui-Zhong Qiu, Zihao Li et al. · 0 citations
#machine learning Preprint Oct 2026

Towards a Learnable Retriever for Textual Graph Question Answering

Textual graph question answering (GraphQA) and graph-based retrieval-augmented generation (GraphRAG) have gained increasing attention as a way to ground large language models (LLMs) on structured knowledge. Despite extensive efforts, existing methods still face two key gaps. The first is an architectural gap: existing...

Kai-Feng Jin, Yu-Chen Yan, Zhichen Zeng et al. · 0 citations

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