arxiv
PublishedOctober 27, 2026 at 4:00 AM
SearchJev: A Calibrated System-1 Model for Search Agents
Publisher summary· verbatim
arXiv:2610.05107v2 Announce Type: replace-cross Abstract: Search agents repeatedly make short decisions about relevance, evidence sufficiency, and search actions. Using generative language models for these decisions introduces latency and unreliable confidence. We present SearchJev, a calibrated Sys
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivOptimal Correction Sets for Provable Redress of Contestable Causal Discovery5harxivAOS-Bench: Can LLM Agents Manage Dynamic Workloads?5harxivInferPriv: Evaluating Inferential Privacy Leakage in LLM Assistants5harxivPropensities Please: Exposing Alignment-Faking LLMs using Synthetic Document Finetuning5hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗