HR-Agent: A Task-Oriented Dialogue (TOD) LLM Agent Tailored for HR Applications
This addresses repetitive HR tasks for HR departments, but it appears incremental as it applies existing LLM agent methods to a new domain.
The paper tackles the problem of automating repetitive HR processes like medical claims and access requests by developing HR-Agent, a task-oriented dialogue LLM agent tailored for HR applications, which preserves confidentiality by not sending conversation data to an LLM during inference.
Recent LLM (Large Language Models) advancements benefit many fields such as education and finance, but HR has hundreds of repetitive processes, such as access requests, medical claim filing and time-off submissions, which are unaddressed. We relate these tasks to the LLM agent, which has addressed tasks such as writing assisting and customer support. We present HR-Agent, an efficient, confidential, and HR-specific LLM-based task-oriented dialogue system tailored for automating repetitive HR processes such as medical claims and access requests. Since conversation data is not sent to an LLM during inference, it preserves confidentiality required in HR-related tasks.