LLM coding agents cannot reach the 10^{-4} relative accuracy required for gravitational wave modeling tasks and show systematic failures including metric misuse and result fabrication.
Villaescusa-Navarro, B
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Analogical reasoning increases LLM solution diversity by 90-173% and novelty rate to over 50%, delivering up to 13-fold gains on biomedical tasks including perturbation prediction and cell communication.
GRAFT-ATHENA projects combinatorial method choices into factored trees that embed as fingerprints in a metric space, enabling an agentic system to accumulate experience across domains and autonomously discover new numerical techniques for physics-informed problems.
In DHOST theories with Gauss-Bonnet and Weyl operators, gauge symmetry invariance conditions are identical to Hamiltonian constraints eliminating ghosts.
GWAgent agentic workflow produces analytic surrogates for eccentric BBH waveforms with 6.9e-4 median mismatch and 8.4x speedup, outperforming baselines, and infers eccentricity for GW200129.
CMBAgent achieves high accuracy on well-specified astrophysical tasks with context but generates silent, plausible-yet-incorrect outputs on reasoning-challenging problems, with no self-diagnosis of inconsistencies.
LARA-HPC introduces a validation-first agentic system with dry-run verification and multi-phase refinement that improves robustness of AI-generated DFT workflows on HPC systems.
citing papers explorer
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gwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy
LLM coding agents cannot reach the 10^{-4} relative accuracy required for gravitational wave modeling tasks and show systematic failures including metric misuse and result fabrication.
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Unlocking LLM Creativity in Science through Analogical Reasoning
Analogical reasoning increases LLM solution diversity by 90-173% and novelty rate to over 50%, delivering up to 13-fold gains on biomedical tasks including perturbation prediction and cell communication.
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GRAFT-ATHENA: Self-Improving Agentic Teams for Autonomous Discovery and Evolutionary Numerical Algorithms
GRAFT-ATHENA projects combinatorial method choices into factored trees that embed as fingerprints in a metric space, enabling an agentic system to accumulate experience across domains and autonomously discover new numerical techniques for physics-informed problems.
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AI--Assisted Exploration: DHOST Theories without Quantum Ghosts
In DHOST theories with Gauss-Bonnet and Weyl operators, gauge symmetry invariance conditions are identical to Hamiltonian constraints eliminating ghosts.
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Discovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves
GWAgent agentic workflow produces analytic surrogates for eccentric BBH waveforms with 6.9e-4 median mismatch and 8.4x speedup, outperforming baselines, and infers eccentricity for GW200129.
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Plausible but Wrong: A case study on Agentic Failures in Astrophysical Workflows
CMBAgent achieves high accuracy on well-specified astrophysical tasks with context but generates silent, plausible-yet-incorrect outputs on reasoning-challenging problems, with no self-diagnosis of inconsistencies.
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LARA: Validation-Driven Agentic Supercomputer Workflows for Atomistic Modeling
LARA-HPC introduces a validation-first agentic system with dry-run verification and multi-phase refinement that improves robustness of AI-generated DFT workflows on HPC systems.