32 citations · 73 across the 28 of their papers we have counts for
10 papers · 1 filter
SimpleDesign: A Joint Model for Protein Sequence and Structure Codesign
Jiarui Lu, Yuyang Wang, Yizhe Zhang +4
Proteins are fundamental to biological processes, with their function determined by the complex interplay between the amino acid sequence and the three-dimensional structure. Devel…
Conditionally Site-Independent Neural Evolution of Antibody Sequences
Stephen Zhewen Lu, Aakarsh Vermani, Kohei Sanno +4
Common deep learning approaches for antibody engineering focus on modeling the marginal distribution of sequences. By treating sequences as independent samples, however, these meth…
COMPASS: Benchmarking Constrained Optimization in LLM Agents
Tian Qin, Felix Bai, Ting-Yao Hu +8
Human decision-making often involves constrained optimization. As LLM agents are deployed to assist with real-world tasks like travel planning, shopping, and scheduling, they must…
SimpleFold: Folding Proteins is Simpler than You Think
Yuyang Wang, Jiarui Lu, Navdeep Jaitly +2
Protein folding models have achieved groundbreaking results typically via a combination of integrating domain knowledge into the architectural blocks and training pipelines. Noneth…
Apple Intelligence Foundation Language Models: Tech Report 2025
Ethan Li, Anders Boesen Lindbo Larsen, Chen Zhang +395
We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services: i a 3B-parameter on-device model opti…
AXLearn: Modular, Hardware-Agnostic Large Model Training
Mark Lee, Chang Lan, Tom Gunter +34
AXLearn is a production system which facilitates scalable and high-performance training of large deep learning models. Compared to other state-of-art deep learning systems, AXLearn…