3 papers
cs.AI2026
RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents
Jize Wang, Han Wu, Zhiyuan You +9
Mixture-of-Agents (MoA) improves LLM performance through layered collaboration, but its dense topology raises costs and latency. Existing methods employ LLM judges to filter respon…
cs.CL2025
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…
cs.CL2024
SAIL: Sample-Centric In-Context Learning for Document Information Extraction
Jinyu Zhang, Zhiyuan You, Jize Wang +1
Document Information Extraction (DIE) aims to extract structured information from Visually Rich Documents (VRDs). Previous full-training approaches have demonstrated strong perform…