10 papers
Wnuan: Staged Post-Training for Question Answering over Proprietary Enterprise Knowledge
Xiaofeng Shi, Xiaosong Qiu, Wenxin Ma +6
Enterprise question answering requires models to acquire proprietary knowledge without discarding general capabilities. We present Wnuan, a three-stage pipeline that constructs tas…
RAFT: Data Refinement and Adaptive Distillation for Domain Fine-Tuning with Alleviated Forgetting
Yuduo Li, Xiaofeng Shi, Qian Kou +2
Domain-specific supervised fine-tuning (SFT) often improves in-domain performance at the cost of degrading a model's general capabilities. We view this degradation through two prac…
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…
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…
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…
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…