Federico Borazio
Papers
1
Total Citations
2
H-Index
1
About
Federico Borazio is a researcher at the forefront of Human-Robot Interaction (HRI), specializing in multi-modal large language models (MLLMs) and grounded natural language understanding. His work bridges the gap between linguistic, visual, and world knowledge, enabling robots to execute complex tasks through more intuitive dialogue. Borazio’s most notable contribution, detailed in his 2025 paper “Training Multi-Modal LLMs through Dialogue Planning for HRI,” introduces an explicit dialogue planning phase that significantly enhances how robots interpret and respond to human commands. This innovative approach has already garnered 2 citations, marking it as a foundational piece in the emerging field of structured, multi-modal communication for robotics. By integrating explicit planning into MLLM training, Borazio addresses a critical challenge in HRI: ensuring that robots not only understand language but also the context and intent behind it. His work is poised to influence the next generation of interactive robots, making them more adaptable and effective in real-world settings. For students and researchers, Borazio’s research offers a compelling glimpse into how advanced AI can transform human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Training Multi-Modal LLMs through Dialogue Planning for HRI2 citations · 2025