Glad to share our recently accepted ACM #SIGMOD2027 paper. In this work, we introduce a cost-efficient RAG for entity matching that reduces computational overhead through blocking-based batch processing for retrieval and generation. #DataIntegration #EntityMatching #GraphRAG arxiv.org/abs/2602.05708
October 16, 2026 at 6:02 PM
Glad to share our recently accepted ACM #SIGMOD2027 paper. In this work, we introduce a cost-efficient RAG for entity matching that reduces computational overhead through blocking-based batch processing for retrieval and generation. #DataIntegration #EntityMatching #GraphRAG arxiv.org/abs/2602.05708
Temperature scaling cut Expected Calibration Error by up to 23.83% for RoBERTa on four entity‑matching benchmarks, where uncalibrated ECE ranged from 0.0043 to 0.0552. https://getnews.me/confidence-calibration-improves-large-language-model-entity-matching/ #entitymatching #calibration #llm
September 26, 2025 at 2:40 PM
Temperature scaling cut Expected Calibration Error by up to 23.83% for RoBERTa on four entity‑matching benchmarks, where uncalibrated ECE ranged from 0.0043 to 0.0552. https://getnews.me/confidence-calibration-improves-large-language-model-entity-matching/ #entitymatching #calibration #llm