Philipp Sadler — accepted AI-conference papers

2025

Playpen: An Environment for Exploring Learning From Dialogue Game Feedback

Nicola Horst, Davide Mazzaccara, Antonia Schmidt, Michael Sullivan, Filippo Moment{\`e}, Luca Franceschetti +10

EMNLP 2025

Interaction between learner and feedback-giver has come into focus recently for post-training of Large Language Models (LLMs), through the use of reward models that judge the appropriateness of a model’s response. In this paper, we investigate whether Dialogue Games—goal-directed and rule-governed a

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗

2024

Sharing the Cost of Success: A Game for Evaluating and Learning Collaborative Multi-Agent Instruction Giving and Following Policies

Philipp Sadler, Sherzod Hakimov, David Schlangen

COLING 2024main

In collaborative goal-oriented settings, the participants are not only interested in achieving a successful outcome, but do also implicitly negotiate the effort they put into the interaction (by adapting to each other). In this work, we propose a challenging interactive reference game that requires…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗

2023

Yes, this Way! Learning to Ground Referring Expressions into Actions with Intra-episodic Feedback from Supportive Teachers

Philipp Sadler, Sherzod Hakimov, David Schlangen

ACL 2023findings

The ability to pick up on language signals in an ongoing interaction is crucial for future machine learning models to collaborate and interact with humans naturally. In this paper, we present an initial study that evaluates intra-episodic feedback given in a collaborative setting. We use a referenti…

Cited by 2 Source ↗PDF ↗code ↗Scholar ↗

2023

clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents

Kranti CH, Jana Götze, Sherzod Hakimov, Brielen Madureira, Philipp Sadler, David Schlangen

EMNLP 2023long main

Recent work has proposed a methodology for the systematic evaluation of "Situated Language Understanding Agents" --- agents that operate in rich linguistic and non-linguistic contexts --- through testing them in carefully constructed interactive settings. Other recent work has argued that Large Lang…

Cited by 62 Source ↗code ↗Scholar ↗