Citation-Driven Multi-View Training for Patent Embeddings: QaECTER and Sophia-Bench
Patent retrieval underpins critical decisions in innovation, examination, and IP strategy, yet progress has been hampered by the absence of benchmarks that reflect the diversity of real world search scenarios. We address this gap with two contributions. First, we introduce Sophiabench, a large-scale patent retrieval benchmark comprising 10,000 queries and 75,000 corpus documents stratified across ten years, eight IPC technology sections, and twelve filing jurisdictions. Unlike prior benchmarks, Sophia-bench tests retrieval using 12 different query types-from structured patent fields to AI-generated summaries-and evaluates results against citation-based ground truth enhanced with a novel d...
| Authors | Younes Djemmal, You Zuo, Kim Gerdes et al. |
|---|---|
| Primary category | cs.IR |
| Published | 24 April 2026 |
| Last updated at source | 24 April 2026 |
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