Papers by Jana Götze

2 papers
clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents (2023.emnlp-main)

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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 .
The slurk Interaction Server Framework: Better Data for Better Dialog Models (2022.lrec-1)

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Challenge: slurk is a lightweight dialog data collection and testing tool for crowdsourcing platforms.
Approach: They present a lightweight dialog server that allows to set up dialog data collections and run experiments.
Outcome: The slurk software allows to set up dialog data collections and run experiments with no limitations on the number of participants.

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