LLM-Supported Hybrid Reranking Architecture for Candidate-Job Matching in Recruitment Processes
This study proposes a hybrid architecture that integrates vector-based semantic search with data validation steps and delivers the final decision through a large language model-based reranking module to overcome problems with traditional applicant tracking systems and pure large language model methods.