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#multi-turn evaluation

multi-turn evaluation

1 पेपर

A child-safety research team studies branching multi-turn dialogue traces behind a protected classroom observation window without showing harmful content
कॉन्फ्रेंस पेपर2025
कॉन्फ्रेंस पेपर 66

Child-specific multi-turn red teaming found safety gaps that adult baselines and single-turn tests missed

Prasanjit Rath, Hari Shrawgi, Parag Agrawal, Sandipan Dandapat

NAACL 2025 Industry Track

Rath and colleagues created 560 synthetic child personas and matched adult baselines to red-team six language-model snapshots over five-turn conversations. The benchmark found substantially higher defect rates for child scenarios in several categories and showed that many failures emerged only after the dialogue developed.

child safetylarge language modelsred teaming
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