Author

Lars Benedikt Kaesberg

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Jul 2026

Can Agents Deceive? Evaluating Reasoning and Deception in ParliamentBench using a Social Deduction Game

This work presents the open-source benchmark framework ParliamentBench based on the game Secret Hitler to evaluate LLMs in scenarios that require deception, persuasion, and reasoning under information asymmetry, and introduces three novel metrics that isolate social deduction, reasoning, and deceptive consistency.

Niklas Bauer, Lars Benedikt Kaesberg, Akiko Aizawa et al. · arXiv.org · 0 citations

Preprint Aug 2026

Is Visual Prompting All You Need? Studying VLM Spatial Reasoning under Progressive Visual Scaffolds

It is found that visual presentation is a central factor that determines whether VLM benchmarks measure grounded perception, downstream reasoning, or a mixture of both, and gains are closely tied to reductions in grounding-related errors, while rule reasoning remains comparatively challenging.

Lars Benedikt Kaesberg, Tianyu Yang, F. Wunderlich et al. · 0 citations

Preprint Jul 2026

Decision Protocols in Multi-Agent Large Language Model Conversations

This thesis introduces the Multi-Agent LLM (MALLM) framework, which implements and evaluates various decision protocols, namely voting, consensus, and judge decision mechanisms, to simulate multi-agent discussions for conversational task solving and indicates that consensus protocols excel in knowledge-intensive domain...

Lars Benedikt Kaesberg · 0 citations