AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model

Abstract

Seungwhan Moon, Andrea Madotto, Zhaojiang Lin, Tushar Nagarajan, Matt Smith, Shashank Jain, Chun-Fu Yeh, Prakash Murugesan, Peyman Heidari, Yue Liu, Kavya Srinet, Babak Damavandi, Anuj Kumar. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track. 2024.