Prospective Experiment for Reinforcement Learning on Demand Response in a Social Game Framework. - Lucas Spangher; Akash Gokul; Manan Khattar; Joseph Palakapilly; Akaash Tawade; Adam Bouyamourn; Alex Devonport; Costas J. Spanos (e-Energy, 2020)

Pricing in Prosumer Aggregations using Reinforcement Learning. - Utkarsha Agwan; Lucas Spangher; William F. Arnold; Tarang Srivastava; Kameshwar Poolla; Costas J. Spanos (e-Energy, 2021)

Adapting Surprise Minimizing Reinforcement Learning Techniques for Transactive Control. - William F. Arnold; Tarang Srivastava; Lucas Spangher; Utkarsha Agwan; Costas J. Spanos (e-Energy, 2021)

Using Meta Reinforcement Learning to Bridge the Gap between Simulation and Experiment in Energy Demand Response. - Doseok Jang; Lucas Spangher; Manan Khattar; Utkarsha Agwan; Costas J. Spanos (e-Energy, 2021)

Offline-online reinforcement learning for generalizing demand response price-setting to energy systems. - Doseok Jang; Lucas Spangher; Manan Khattar; Utkarsha Agwan; Selvaprabuh Nadarajah; Costas J. Spanos (BuildSys, 2021)

Offline-online reinforcement learning for energy pricing in office demand response: lowering energy and data costs. - Doseok Jang; Lucas Spangher; Tarang Srivastava; Manan Khattar; Utkarsha Agwan; Selvaprabu Nadarajah; Costas J. Spanos (BuildSys, 2021)

Transactive multi-agent reinforcement learning for distributed energy price localization. - Lucas Spangher (BuildSys, 2021)

Offline-Online Reinforcement Learning for Energy Pricing in Office Demand Response: Lowering Energy and Data Costs. - Doseok Jang; Lucas Spangher; Manan Khattar; Utkarsha Agwan; Selvaprabuh Nadarajah; Costas J. Spanos (CoRR, 2021)

Adversarial poisoning attacks on reinforcement learning-driven energy pricing. - Sam Gunn; Doseok Jang; Orr Paradise; Lucas Spangher; Costas J. Spanos (BuildSys, 2022)

Personalized Federated Hypernetworks for Privacy Preservation in Multi-Task Reinforcement Learning. - Doseok Jang; Larry Yan; Lucas Spangher; Costas J. Spanos (CoRR, 2022)

Machine Learning for Smart and Energy-Efficient Buildings. - Hari Prasanna Das; Yu-Wen Lin; Utkarsha Agwan; Lucas Spangher; Alex Devonport; Yu Yang 008; Ján Drgona; Adrian Chong; Stefano Schiavon; Costas J. Spanos (CoRR, 2022)

Personalized Federated Hypernetworks for Multi-Task Reinforcement Learning in Microgrid Energy Demand Response. - Doseok Jang; Lucas Spangher; Tarang Srivastava; Larry Yan; Costas J. Spanos (BuildSys, 2023)

Continuous Convolutional Neural Networks for Disruption Prediction in Nuclear Fusion Plasmas. - William F. Arnold; Lucas Spangher; Christina Rea (CoRR, 2023)

Active Reinforcement Learning for Robust Building Control. - Doseok Jang; Larry Yan; Lucas Spangher; Costas J. Spanos (AAAI, 2024)

Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy. - Lucas Spangher; Allen M. Wang; Andrew Maris; Myles Stapelberg; Viraj Mehta; Alex Saperstein; Stephen Lane-Walsh; Akshata Kishore Moharir; Alessandro Pau; Cristina Rea (ICML, 2024)

Offline Regularised Reinforcement Learning for Large Language Models Alignment. - Pierre Harvey Richemond; Yunhao Tang; Daniel Guo 001; Daniele Calandriello; Mohammad Gheshlaghi Azar; Rafael Rafailov; Bernardo Ávila Pires; Eugene Tarassov; Lucas Spangher; Will Ellsworth; Aliaksei Severyn; Jonathan Mallinson; et al. (CoRR, 2024)

Time Series Viewmakers for Robust Disruption Prediction. - Dhruva Chayapathy; Tavis Siebert; Lucas Spangher; Akshata Kishore Moharir; Om Manoj Patil; Cristina Rea (CoRR, 2024)

Project MPG: towards a generalized performance benchmark for LLM capabilities. - Lucas Spangher; Tianle Li; William F. Arnold; Nick Masiewicki; Xerxes Dotiwalla; Rama Parusmathi; Peter Grabowski; Eugene Ie; Daniel Gruhl (CoRR, 2024)

Chatbot Arena Estimate: towards a generalized performance benchmark for LLM capabilities. - Lucas Spangher; Tianle Li; William F. Arnold; Nick Masiewicki; Xerxes Dotiwalla; Rama Kumar Pasumarthi; Peter Grabowski; Eugene Ie; Daniel Gruhl (NAACL (Industry Track), 2025)

Factored Agents: Decoupling In-Context Learning and Memorization for Robust Tool Use. - Nicholas Roth; Christopher Hidey; Lucas Spangher; William F. Arnold; Chang Ye; Nick Masiewicki; Jinoo Baek; Peter Grabowski; Eugene Ie (CoRR, 2025)

Revisiting Funnel Transformers for Modern LLM Architectures with Comprehensive Ablations in Training and Inference Configurations. - DongHyun Choi; Lucas Spangher; Chris Hidey; Peter Grabowski; Ramy Eskander (CoRR, 2025)