MM‑WebAgent is a hierarchical agent that jointly plans layout and multimodal assets, then iteratively refines them, achieving state‑of‑the‑art results on a new multimodal webpage generation benchmark.

The paper introduces a formal resource‑allocation framework for serving large transformer‑based models with pipeline parallelism, proposing greedy placement, cache allocation, and load‑balancing algorithms that drastically cut inference latency.

LR‑Robot is a human‑in‑the‑loop framework that leverages expert taxonomies and LLMs to perform scalable, reliable systematic literature reviews of financial research, demonstrated on a large option‑pricing corpus.

This paper empirically evaluates AI‑assisted requirements engineering against expert judgments, showing AI can reliably handle initial quality checks but still relies on human expertise for deeper analysis.

This paper provides a comprehensive literature review on the application of Large Language Models (LLMs) in business process modeling, detailing their current integration into text-to-model pipelines and identifying key challenges and future research directions for supporting complex organizational process modeling.