2 papers
cs.AI2025
Boosting Process-Correct CoT Reasoning by Modeling Solvability of Multiple-Choice QA
Raphael Schumann, Stefan Riezler
Reasoning quality in large language models depends not only on producing correct answers but also on generating valid intermediate steps. We study this through multiple-choice ques…
cs.AI2024
VELMA: Verbalization Embodiment of LLM Agents for Vision and Language Navigation in Street View
Raphael Schumann, Wanrong Zhu, Weixi Feng +3
Incremental decision making in real-world environments is one of the most challenging tasks in embodied artificial intelligence. One particularly demanding scenario is Vision and L…