PaperRouter-Agent: Training-Free LLM Agent for Personalized Paper Routing

Jul 14, 2026

Researchers introduce PaperRouter-Agent, a training-free large language model (LLM) agent designed to route new academic papers into user-specific folder hierarchies by grounding its decisions in the content of folder members rather than relying solely on folder names. In tests on real personal libraries, PaperRouter-Agent improved Recall@1 from 0.39 to 0.61 and Recall@3 from 0.57 to 0.83. On the public LaMP-2 benchmark, it increased accuracy from 44.5% to 51.5% and macro-F1 by 9.0 points over a single-shot baseline.

Why it matters: This work demonstrates a significant advance in personalized information organization, showing that LLM agents can effectively route papers in reference managers without per-user training.

Full story at: arXiv Information Retrieval ↗