In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration
Summary: In-context clustering: prompt LLMs to cluster record sets directly (vs pairwise), reducing API calls/time and improving scalability. LLM-CER maps the design space (set size, diversity, ordering), adds cluster-merging and hallucination mitigation, yielding up to 150% accuracy gains and 5× fewer API calls. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Jiajie Fu
- 2. Haitong Tang
- 3. Arijit Khan
- 4. Sharad Mehrotra
- 5. Xiangyu Ke
- 6. Yunjun Gao
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