3 citations · 5 across the 6 of their papers we have counts for
7 papers
Instruction-Tuned LLMs for Parsing and Mining Unstructured Logs on Leadership HPC Systems
Ahmad Maroof Karimi, Jong Youl Choi, Charles Qing Cao +1
Leadership-class HPC systems generate massive volumes of heterogeneous, largely unstructured system logs. Because these logs originate from diverse software, hardware, and runtime…
Global Attention with Linear Complexity for Exascale Generative Data Assimilation in Earth System Prediction
Xiao Wang, Zezhong Zhang, Isaac Lyngaas +10
Accurate Earth system prediction requires state inference from incomplete observations, but conventional two-stage data assimilation (DA) is computationally prohibitive because rep…
Multi-task parallelism for robust pre-training of graph foundation models on multi-source, multi-fidelity atomistic modeling data
Massimiliano Lupo Pasini, Jong Youl Choi, Pei Zhang +6
Graph foundation models using graph neural networks promise sustainable, efficient atomistic modeling. To tackle challenges of processing multi-source, multi-fidelity data during p…
Exploring the Capabilities of the Frontier Large Language Models for Nuclear Energy Research
Ahmed Almeldein, Mohammed Alnaggar, Rick Archibald +47
The AI for Nuclear Energy workshop at Oak Ridge National Laboratory evaluated the potential of Large Language Models (LLMs) to accelerate fusion and fission research. Fourteen inte…
ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling
Xiao Wang, Jong-Youl Choi, Takuya Kurihaya +15
Sparse observations and coarse-resolution climate models limit effective regional decision-making, underscoring the need for robust downscaling. However, existing AI methods strugg…
Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier
Aristeidis Tsaris, Chengming Zhang, Xiao Wang +9
Vision Transformers (ViTs) are pivotal for foundational models in scientific imagery, including Earth science applications, due to their capability to process large sequence length…
ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability
Xiao Wang, Siyan Liu, Aristeidis Tsaris +8
Earth system predictability is challenged by the complexity of environmental dynamics and the multitude of variables involved. Current AI foundation models, although advanced by le…