19 citations · 19 across the 2 of their papers we have counts for
3 papers
SMIR: Efficient Synthetic Data Pipeline To Improve Multi-Image Reasoning
Andrew Li, Rahul Thapa, Rahul Chalamala +3
Vision-Language Models (VLMs) excel at understanding single images, aided by high-quality instruction datasets. However, multi-image reasoning remains underexplored in the open-sou…
RedPajama: an Open Dataset for Training Large Language Models
Maurice Weber, Daniel Fu, Quentin Anthony +16
Large language models are increasingly becoming a cornerstone technology in artificial intelligence, the sciences, and society as a whole, yet the optimal strategies for dataset co…
LoLCATs: On Low-Rank Linearizing of Large Language Models
Michael Zhang, Simran Arora, Rahul Chalamala +5
Recent works show we can linearize large language models (LLMs) -- swapping the quadratic attentions of popular Transformer-based LLMs with subquadratic analogs, such as linear att…