Papers by Katie Baker
AlanaVLM: A Multimodal Embodied AI Foundation Model for Egocentric Video Understanding (2024.findings-emnlp)
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Alessandro Suglia, Claudio Greco, Katie Baker, Jose Part, Ioannis Papaioannou, Arash Eshghi, Ioannis Konstas, Oliver Lemon
| Challenge: | Current Vision-Language Models (VLMs) focus on third-person view videos, neglecting the richness of egocentric perceptual experience. |
| Approach: | They propose to use the Egocentric Video Understanding Dataset (EVUD) to train VLMs on video captioning and question answering tasks specific to egocentric videos. |
| Outcome: | The proposed model outperforms open-source models including strong Socratic models using GPT-4 as a planner by 3.6% and outperformed Claude 3 and Gemini Pro Vision 1.0. |