Evaluating Language Model Agency through Negotiations

arXiv:2401.04536v2 Announce Type: replace-cross
Abstract: We introduce an approach to evaluate language model (LM) agency using negotiation games. This approach better reflects real-world use cases and addresses some of the shortcomings of alternative LM benchmarks. Negotiation games enable us to study multi-turn, and cross-model interactions, modulate complexity, and side-step accidental evaluation data leakage. We use our approach to test six widely used and publicly accessible LMs, evaluating performance and alignment in both self-play and cross-play settings. Noteworthy findings include: (i) …

abstract agency arxiv benchmarks cases complexity cs.ai cs.cl cs.lg data data leakage evaluation games interactions language language model modulate negotiation negotiations study through type use cases world