8 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.CL2023
GRASP: A novel benchmark for evaluating language GRounding And Situated Physics understanding in multimodal language models
Serwan Jassim, Mario Holubar, Annika Richter +3
This paper presents GRASP, a novel benchmark to evaluate the language grounding and physical understanding capabilities of video-based multimodal large language models (LLMs). This…
cs.LG2020★ 8 cited
Continuous-action Reinforcement Learning for Playing Racing Games: Comparing SPG to PPO
Mario S. Holubar, Marco A. Wiering
In this paper, a novel racing environment for OpenAI Gym is introduced. This environment operates with continuous action- and state-spaces and requires agents to learn to control t…