QMP-Bench supplies a realistic test set for AI on quantum many-body problems while PhysVEC uses integrated verifiers to turn unreliable LLM generations into code that passes both syntax and physics checks, outperforming baselines.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 3
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 3representative citing papers
Positive running of the spectral index is achievable in Einstein-Gauss-Bonnet gravity with viable inflation, unlike standard scalar field and F(R) models which face challenges.
MCMC analysis of sixteen ghost-free f(R,G) inflation models shows all reproduce ns ≈ 0.97 at 60 e-folds with stable μ ≈ 0.1, preference set by Hubble parametrization.
Reheating temperature and equation-of-state parameter assumptions in Weyl-invariant Einstein-Cartan gravity models significantly alter predicted inflationary observables.
citing papers explorer
-
Towards Verifiable and Self-Correcting AI Physicists for Quantum Many-Body Simulations
QMP-Bench supplies a realistic test set for AI on quantum many-body problems while PhysVEC uses integrated verifiers to turn unreliable LLM generations into code that passes both syntax and physics checks, outperforming baselines.
-
Positive Running of the Spectral Index for Scalar Theory and Modified Gravity
Positive running of the spectral index is achievable in Einstein-Gauss-Bonnet gravity with viable inflation, unlike standard scalar field and F(R) models which face challenges.
-
String-inspired Gauss-Bonnet Gravity Inflation and ACT
MCMC analysis of sixteen ghost-free f(R,G) inflation models shows all reproduce ns ≈ 0.97 at 60 e-folds with stable μ ≈ 0.1, preference set by Hubble parametrization.
-
Reheating in geometric Weyl-invariant Einstein-Cartan gravity
Reheating temperature and equation-of-state parameter assumptions in Weyl-invariant Einstein-Cartan gravity models significantly alter predicted inflationary observables.