2 citations · 4 across the 6 of their papers we have counts for
5 papers · 1 filter
Data Whisperer: Efficient Data Selection for Task-Specific LLM Fine-Tuning via Few-Shot In-Context Learning
Shaobo Wang, Xiangqi Jin, Ziming Wang +8
Fine-tuning large language models (LLMs) on task-specific data is essential for their effective deployment. As dataset sizes grow, efficiently selecting optimal subsets for trainin…
Neuro-Symbolic Query Compiler
Yuyao Zhang, Zhicheng Dou, Xiaoxi Li +5
Precise recognition of search intent in Retrieval-Augmented Generation (RAG) systems remains a challenging goal, especially under resource constraints and for complex queries with…
Hierarchical Document Refinement for Long-context Retrieval-augmented Generation
Jiajie Jin, Xiaoxi Li, Guanting Dong +6
Real-world RAG applications often encounter long-context input scenarios, where redundant information and noise results in higher inference costs and reduced performance. To addres…
RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation
Xiaoxi Li, Jiajie Jin, Yujia Zhou +4
Large language models (LLMs) exhibit remarkable generative capabilities but often suffer from hallucinations. Retrieval-augmented generation (RAG) offers an effective solution by i…
TechGPT-2.0: A large language model project to solve the task of knowledge graph construction
Jiaqi Wang, Yuying Chang, Zhong Li +6
Large language models have exhibited robust performance across diverse natural language processing tasks. This report introduces TechGPT-2.0, a project designed to enhance the capa…