45 citations · 129 across the 21 of their papers we have counts for
21 papers
Position: AI Agents in Scientific Teams Should Be Studied as Human-Agent Systems
Patrick Emami, Sameera Horawalavithana, Truc Nguyen +11
Large language model-based agents are increasingly deployed as collaborators in scientific discovery yet most current work focuses on the autonomous capabilities of "AI Scientists"…
A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners
Patrick Emami, Nan Qiang, Peter Graf
Supervised fine-tuning (SFT) improves end-to-end classical planning in large language models (LLMs), but do these models also learn to represent and reason about the planning probl…
SCICONVBENCH: Benchmarking LLMs on Multi-Turn Clarification for Task Formulation in Computational Science
Nithin Somasekharan, Youssef Hassan, Shiyao Lin +5
Large Language Models (LLMs) are increasingly deployed as scientific AI as- sistants, and a growing body of benchmarks evaluates their capabilities across knowledge retrieval, reas…
Evaluating Memory Condensation Strategies for Coding Agents in Data-Driven Scientific Discovery
Renuka Chintalapati, Sid Raskar, Anurag Acharya +3
Coding agents accumulate extensive context during long-running tasks, yet fixed context windows force practitioners to choose between truncation and task failure. While numerous me…
Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials
Steven R. Spurgeon, Milad Abolhasani, Frederick Baddour +28
Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising systems never reach deployment…
Conditional Distribution Estimation of Building Characteristics with Diffusion Models for Urban Energy Modeling
Saumya Sinha, Alexandre Cortiella, Rawad El Kontar +3
Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models…