作者位次 #3/3ACL 2026Poster· Natural Language Processing
Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorization
Gongbo Zhang · Yifan Peng · Chunhua Weng
摘要
Retrieval-Augmented Generation (RAG) improves the factual accuracy of large language model (LLM) outputs by grounding generation in external knowledge. Recent agentic RAG systems extend this paradigm by introducing critic agents that evaluate model responses and iteratively refine outputs. Howeve...