3 citations · 3 across the 3 of their papers we have counts for
4 papers
Revisiting Funnel Transformers for Modern LLM Architectures with Comprehensive Ablations in Training and Inference Configurations
DongHyun Choi, Lucas Spangher, Chris Hidey +2
Transformer-based Large Language Models, which suffer from high computational costs, advance so quickly that techniques proposed to streamline earlier iterations are not guaranteed…
Factored Agents: Decoupling In-Context Learning and Memorization for Robust Tool Use
Nicholas Roth, Christopher Hidey, Lucas Spangher +6
In this paper, we propose a novel factored agent architecture designed to overcome the limitations of traditional single-agent systems in agentic AI. Our approach decomposes the ag…
Project MPG: towards a generalized performance benchmark for LLM capabilities
Lucas Spangher, Tianle Li, William F. Arnold +6
There exists an extremely wide array of LLM benchmarking tasks, whereas oftentimes a single number is the most actionable for decision-making, especially by non-experts. No such ag…
Time Series Viewmakers for Robust Disruption Prediction
Dhruva Chayapathy, Tavis Siebert, Lucas Spangher +3
Machine Learning guided data augmentation may support the development of technologies in the physical sciences, such as nuclear fusion tokamaks. Here we endeavor to study the probl…