5 papers
AgenticOCR: Parsing Only What You Need for Efficient Retrieval-Augmented Generation
Zhengren Wang, Dongsheng Ma, Huaping Zhong +4
The expansion of retrieval-augmented generation (RAG) into multimodal domains has intensified the challenge for processing complex visual documents, such as financial reports. Whil…
DocDancer: Towards Agentic Document-Grounded Information Seeking
Qintong Zhang, Xinjie Lv, Jialong Wu +8
Document Question Answering (DocQA) focuses on answering questions grounded in given documents, yet existing DocQA agents lack effective tool utilization and largely rely on closed…
DOCR-Inspector: Fine-Grained and Automated Evaluation of Document Parsing with VLM
Qintong Zhang, Junyuan Zhang, Zhifei Ren +8
Document parsing aims to transform unstructured PDF images into semi-structured data, facilitating the digitization and utilization of information in diverse domains. While vision…
Can LLMs be Good Graph Judge for Knowledge Graph Construction?
Haoyu Huang, Chong Chen, Zeang Sheng +2
In real-world scenarios, most of the data obtained from the information retrieval (IR) system is unstructured. Converting natural language sentences into structured Knowledge Graph…
OCR Hinders RAG: Evaluating the Cascading Impact of OCR on Retrieval-Augmented Generation
Junyuan Zhang, Qintong Zhang, Bin Wang +6
Retrieval-augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external knowledge to reduce hallucinations and incorporate up-to-date information without…