Open-Jev Judgments on CallScreenBench: Calibrated One-Pass Scam Screening with a Small Language Model
Screening a phone call for fraud needs a trustworthy probability after every caller turn, in milliseconds. Jev-style typed decisions promise exactly that: declared options go in, one calibrated probability per option comes out of a single forward pass, with no generated text. We test an open implementation of this readout, JevLite, on scam-call screening: Qwen3-4B is LoRA-tuned so that the temperature-scaled softmax over two answer-label logits is P(scam). On 41 held-out CallScreenBench scenarios (577 per-turn decisions) a three-seed ensemble reaches AUROC .974 with calibration error .052, non-inferior to an LLM judge (MiniMax-M3) at a pre-registered .02 margin, with no false alarms on le...
| Authors | Simiao Ren, Kidus Zewde, Xingyu Shen et al. |
|---|---|
| Primary category | cs.CL |
| Published | 21 September 2026 |
| Last updated at source | 21 September 2026 |
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