New Research Explores LLM Applications in Forecasting, Healthcare Guidelines, and Mathematical Proofs

Three arXiv papers examine LLMs for retail forecasting monitoring, clinical guideline queries, and inequality theorem proving.

New Research Explores LLM Applications Across Multiple Domains

Three recent papers on arXiv demonstrate diverse applications of Large Language Models in specialized fields.

Forecast Monitoring System

According to arXiv paper 2512.12059v1, researchers propose “The Forecast Critic,” a system that leverages LLMs for automated forecast monitoring. The paper focuses on identifying poor forecasts in large-scale retail businesses, where monitoring forecasting systems is described as “critical for customer satisfaction, profitability, and operational efficiency.”

Clinical Guidelines Retrieval

ArXiv paper 2510.02967v3 presents a Retrieval-Augmented Generation (RAG) system designed to query the United Kingdom’s National Institute for Health and Care Excellence (NICE) clinical guidelines. The system aims to ground LLMs in clinical evidence by enabling queries of established healthcare guidelines.

Mathematical Inequality Proving

Researchers in arXiv paper 2506.07927v3 address inequality proving using LLMs. According to the abstract, inequality proving is “crucial across diverse scientific and mathematical fields” and tests “advanced reasoning skills such as discovering tight bounds and strategic theorem application,” making it a “distinct, demanding frontier for large language models.”

All three papers represent ongoing efforts to apply LLM capabilities to domain-specific challenges requiring accuracy and specialized knowledge.