arXiv Machine Learning By Jacob Eisenstein, Fantine Huot, Adam Fisch, Jonathan Berant, Mirella Lapata

MT-PingEval: Evaluating Multi-Turn Collaboration with Private Information Games

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arXiv:2602. 24188v2 Announce Type: replace-cross Abstract: We present a scalable and verifiable methodology for evaluating language models in multi-turn interactions, using a suite of collaborative games that require effective communication about private information.

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