clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents (2023.emnlp-main)
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Kranti Chalamalasetti, Jana Götze, Sherzod Hakimov, Brielen Madureira, Philipp Sadler, David Schlangen
| Challenge: | Recent work suggests large language models can be understood as (simulators of) such agents. |
| Approach: | They propose a method for systematic evaluation of "Situated Language Understanding Agents" they propose implementing a framework for implementing rules to be played in "self-play" |
| Outcome: | The proposed model can be evaluated in game-like settings, the authors show . they show that the model can follow game-play instructions and perform better than existing models . |
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