5 papers
Atomistic Language Models Understand and Generate Materials
Sathya Edamadaka, Krithik Ramesh, Ju Li +1
Atomistic structure and natural language have long been modeled separately, with language models either calling atomistic models as tools or being fine-tuned on lossy textual encod…
Deterministic access to global viral sequence data enables robust agentic scientific discovery
Ferdous Nasri, Sarah Gurev, Patrick Varilly +6
Public viral genome resources such as the National Center for Biotechnology Information (NCBI) Virus database are central to outbreak response, evolutionary analysis, vaccine desig…
A Multi-Modal Deep Learning Framework for Colorectal Pathology Diagnosis: Integrating Histological and Colonoscopy Data in a Pilot Study
Krithik Ramesh, Ritvik Koneru
Colorectal diseases, including inflammatory conditions and neoplasms, require quick, accurate care to be effectively treated. Traditional diagnostic pipelines require extensive pre…
Lyra: An Efficient and Expressive Subquadratic Architecture for Modeling Biological Sequences
Krithik Ramesh, Sameed M. Siddiqui, Albert Gu +2
Deep learning architectures such as convolutional neural networks and Transformers have revolutionized biological sequence modeling, with recent advances driven by scaling up found…
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…