Yang Xiang

Papers

Total Citations

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About

Yang Xiang is an emerging researcher working at the intersection of artificial intelligence, natural language processing, and robotic process automation (RPA). His work focuses on leveraging large language models (LLMs) to solve practical, domain-specific challenges in automated systems. His most notable contribution to date is a 2023 study introducing a novel methodology for constructing domain-specific knowledge bases to enhance the performance of ChatGLM — a large language model — specifically for RPA robot code generation. This research addresses a critical challenge in the field: how to improve LLM performance in specialized industrial contexts without incurring prohibitive computational costs. By grounding the model in curated, domain-relevant knowledge, Xiang's approach offers a cost-effective pathway to deploying AI in automation workflows, a problem of growing relevance as enterprises increasingly adopt intelligent automation. Though still in the early stages of building his citation record, with 2 citations on his leading paper, Xiang's research sits at a timely and rapidly expanding frontier where LLM capabilities meet real-world automation needs, positioning him as a researcher to watch in applied AI and enterprise automation.