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SearchJev: A Fast and Calibrated System-1 Model for Search Agents

Hugging Face Daily Papers ↗ · 2026-10-04 Cached

SearchJev introduces a fast, calibrated System-1 model for search agents that scores legal decisions without autoregressive generation, using Soft-Label Learning for Calibrated Decisions (SLCD) to reduce latency and improve confidence reliability. A dual-system agent combining SearchJev with a System-2 model achieves up to 4.7x speedups on BrowseComp-Plus while raising answer accuracy from 45% to 54%.

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