The papers were on foundation world models and language-enhanced OOD. The audience response was, reportedly, positive and encouraged the implementation on physical robotic systems. Citations:
- Zhenjiang Mao, Dong-You Jhong, Ao Wang, Ivan Ruchkin. Language-Enhanced Latent Representations for Out-of-Distribution Detection in Autonomous Driving [Arxiv] [Slides]. Robot Trust for Symbiotic Societies (RTSS) Workshop (co-located with ICRA 2024), Yokohama, Japan, 2024.
- Zhenjiang Mao, Siqi Dai, Yuang Geng, Ivan Ruchkin. Zero-shot Safety Prediction for Autonomous Robots with Foundation World Models [Arxiv] [Poster]. Late-breaking results posters at ICRA 2024 and Back to the Future: Robot Learning Going Probabilistic Workshop (co-located with ICRA 2024), Yokohama, Japan, 2024.