Quality-Controlled Reply and Summary Data for Post-Training Small Language Models in AI Call-Screening Agents
Small language models have improved to the point where a phone can plausibly screen its own calls, answering on an absent owner's behalf without sending call content off the device, a privacy-respecting alternative to cloud call handling. Realizing that promise takes a model that can do two things well: reply within the owner's authority during the call, and afterward tell the owner what happened and what needs attention. Released small models do neither reliably - they raise unwarranted alarms about ordinary callers and write summaries that drop material conditions or report a caller's claims as fact - and real calls supply no reference replies or summaries to learn from. We construct su...
| Authors | Jiaqi Gan, Tsang Ng, Ankit Raj et al. |
|---|---|
| Primary category | cs.CL |
| Published | 18 October 2026 |
| Last updated at source | 18 October 2026 |
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