11 citations · 12 across the 5 of their papers we have counts for
6 papers
Accelerating VLA Inference with Perturbation Informed Execution
Jehun Lee, Hajun Lee, Jimin Ryu +4
Action-chunking vision-language-action (VLA) models predict sequences of future robot actions. Under fixed-horizon execution, the robot executes a fixedlength prefix of each predic…
Fold-CP: A Context Parallelism Framework for Biomolecular Modeling
Dejun Lin, Simon Chu, Vishanth Iyer +35
Understanding cellular machinery requires atomic-scale reconstruction of large biomolecular assemblies. However, predicting the structures of these systems has been constrained by…
SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models
Hyeonbeom Choi, Daechul Ahn, Youhan Lee +3
Vision-Language-Action (VLA) models have emerged as a promising paradigm for general-purpose robotic control, with test-time scaling (TTS) gaining attention to enhance robustness b…
BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery
Peter St. John, Dejun Lin, Polina Binder +89
Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increas…
Solvent: A Framework for Protein Folding
Jaemyung Lee, Kyeongtak Han, Jaehoon Kim +2
Consistency and reliability are crucial for conducting AI research. Many famous research fields, such as object detection, have been compared and validated with solid benchmark fra…
Deep learning models for predicting RNA degradation via dual crowdsourcing
Hannah K. Wayment-Steele, Wipapat Kladwang, Andrew M. Watkins +26
Messenger RNA-based medicines hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limite…