most citedCareBot: A Pioneering Full-Process Open-Source Medical Language Model

1 citations · 1 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2025

Rethinking Supervised Fine-Tuning: Emphasizing Key Answer Tokens for Improved LLM Accuracy

Xiaofeng Shi, Qian Kou, Yuduo Li +1

With the rapid advancement of Large Language Models (LLMs), the Chain-of-Thought (CoT) component has become significant for complex reasoning tasks. However, in conventional Superv…

cs.CL2025

Design, Results and Industry Implications of the World's First Insurance Large Language Model Evaluation Benchmark

Hua Zhou, Bing Ma, Yufei Zhang +1

This paper comprehensively elaborates on the construction methodology, multi-dimensional evaluation system, and underlying design philosophy of CUFEInse v1.0. Adhering to the princ…

cs.IR2025

SPAR: Scholar Paper Retrieval with LLM-based Agents for Enhanced Academic Search

Xiaofeng Shi, Yuduo Li, Qian Kou +3

Recent advances in large language models (LLMs) have opened new opportunities for academic literature retrieval. However, existing systems often rely on rigid pipelines and exhibit…

cs.AI2025

SciSage: A Multi-Agent Framework for High-Quality Scientific Survey Generation

Xiaofeng Shi, Qian Kou, Yuduo Li +5

The rapid growth of scientific literature demands robust tools for automated survey-generation. However, current large language model (LLM)-based methods often lack in-depth analys…

cs.CL20241 cited

CareBot: A Pioneering Full-Process Open-Source Medical Language Model

Lulu Zhao, Weihao Zeng, Xiaofeng Shi +1

Recently, both closed-source LLMs and open-source communities have made significant strides, outperforming humans in various general domains. However, their performance in specific…

cs.CL2024

Smaller Language Models Are Better Instruction Evolvers

Tingfeng Hui, Lulu Zhao, Guanting Dong +3

Instruction tuning has been widely used to unleash the complete potential of large language models. Notably, complex and diverse instructions are of significant importance as they…