3 papers
cs.IR2026
LEDGER: Scaling Agentic Document Editing with Dependency-aware Graph Retrieval
Mike Hang Wang, Utkarsh Garg, Reza Davari +5
We introduce LEDGER to tackle the novel context engineering challenge of agentic document editing, where localized edits to long, structured documents must be applied efficiently w…
cs.CL2024
Developing a Reliable, Fast, General-Purpose Hallucination Detection and Mitigation Service
Song Wang, Xun Wang, Jie Mei +6
Hallucination, a phenomenon where large language models (LLMs) produce output that is factually incorrect or unrelated to the input, is a major challenge for LLM applications that…
cs.CL2024
xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token
Xin Cheng, Xun Wang, Xingxing Zhang +5
This paper introduces xRAG, an innovative context compression method tailored for retrieval-augmented generation. xRAG reinterprets document embeddings in dense retrieval--traditio…