3 citations · 3 across the 8 of their papers we have counts for
9 papers
Accelerating Scientific Research with Gemini: Case Studies and Common Techniques
David P. Woodruff, Vincent Cohen-Addad, Lalit Jain +33
Recent advances in large language models (LLMs) have opened new avenues for accelerating scientific research. While models are increasingly capable of assisting with routine tasks,…
Solving an Open Problem in Theoretical Physics using AI-Assisted Discovery
Michael P. Brenner, Vincent Cohen-Addad, David Woodruff
This paper demonstrates that artificial intelligence can accelerate mathematical discovery by autonomously solving an open problem in theoretical physics. We present a neuro-symbol…
Accelerating scientific discovery with the common task framework
J. Nathan Kutz, Peter Battaglia, Michael Brenner +12
Machine learning (ML) and artificial intelligence (AI) algorithms are transforming and empowering the characterization and control of dynamic systems in the engineering, physical,…
Meshless solutions of PDE inverse problems on irregular geometries
James V. Roggeveen, Michael P. Brenner
Solving inverse and optimization problems over solutions of nonlinear partial differential equations (PDEs) on complex spatial domains is a long-standing challenge. Here we introdu…
Learning constitutive models and rheology from partial flow measurements
Alp M. Sunol, James V. Roggeveen, Mohammed G. Alhashim +2
Constitutive laws relate fluid stress to deformation and underpin predictions of non-Newtonian behavior in industrial and biological fluids. Standard characterization relies on mea…
CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researchers
Haining Pan, James V. Roggeveen, Erez Berg +16
Large language models (LLMs) have shown remarkable progress in coding and math problem-solving, but evaluation on advanced research-level problems in hard sciences remains scarce.…
EEFSUVA: A New Mathematical Olympiad Benchmark
Nicole N Khatibi, Daniil A. Radamovich, Michael P. Brenner
Recent breakthroughs have spurred claims that large language models (LLMs) match gold medal Olympiad to graduate level proficiency on mathematics benchmarks. In this work, we exami…
HARDMath2: A Benchmark for Applied Mathematics Built by Students as Part of a Graduate Class
James V. Roggeveen, Erik Y. Wang, Will Flintoft +42
Large language models (LLMs) have shown remarkable progress in mathematical problem-solving, but evaluation has largely focused on problems that have exact analytical solutions or…
HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics
Jingxuan Fan, Sarah Martinson, Erik Y. Wang +6
Advanced applied mathematics problems are underrepresented in existing Large Language Model (LLM) benchmark datasets. To address this, we introduce HARDMath, a dataset inspired by…