Jingfeng Luo — accepted AI-conference papers

2026

STAR: Similarity-guided Teacher-Assisted Refinement for Super-Tiny Function Calling Models

Jiliang Ni, Jiachen Pu, Zhongyi Yang, Jingfeng Luo, Conggang Hu

ICLR 2026poster

The proliferation of Large Language Models (LLMs) in function calling is pivotal for creating advanced AI agents, yet their large scale hinders widespread adoption, necessitating transferring their capabilities into smaller ones. However, existing paradigms are often plagued by overfitting, training…

Cited by 0 Source ↗code ↗Scholar ↗

2025

DeKeyNLU: Enhancing Natural Language to SQL Generation through Task Decomposition and Keyword Extraction

Jian Chen, Zhenyan Chen, Xuming Hu, Peilin Zhou, Yining Hua, Han Fang +4

EMNLP 2025

Natural Language to SQL (NL2SQL) provides a new model-centric paradigm that simplifies database access for non-technical users by converting natural language queries into SQL commands. Recent advancements, particularly those integrating Retrieval-Augmented Generation (RAG) and Chain-of-Thought (CoT)

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗