Only two of ten advanced AI agents finish a 500-day simulated CEO challenge above the starting cash, and none surpass a hand-tuned rule-based baseline.
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12 Pith papers cite this work, alongside 4,543 external citations. Polarity classification is still indexing.
12
Pith papers citing it
4,543
external citations · OpenAlex
representative citing papers
A finite-sample perspective reveals that inexact likelihood approximations cause under- or over-estimation of posterior spread at intermediate timesteps, leading to early-stopping sensitivity, mode weighting errors, and hallucinations even from multimodal priors alone.
Introduces Lie-Trotter and Strang splitting schemes for explicit pseudo-likelihood MLEs in SDEs with Hölder multiplicative noise, proving strong mean-square convergence, state preservation, consistency, and asymptotic normality of the LT estimator.
A new discrete-time AMM model with diffusive plus jump price processes shows CEX-DEX arbitrage requires volumes comparable to major liquidity pools and produces profits on the scale of total MEV.
NATPS applies time-reversible MASH dynamics within the transition path sampling framework to efficiently generate ensembles of nonadiabatic reactive trajectories on a model system of coupled potential energy surfaces.
BeyondMimic combines compact motion tracking with a unified guided latent diffusion model to master diverse agile behaviors from human demos and solve unseen downstream tasks via test-time classifier guidance.
Heat-kernel smoothing over weighted points on a compact manifold yields a scale-dependent geometric effective sample size that discounts nearby and duplicate particles.
An entity-graph MARL framework (RACHE) using R-GCN message passing and attention pooling over train-service nodes outperforms baseline algorithms in railway pricing revenue across two simulated market scenarios.
MetaRL pre-trained on GBWM problems delivers near-optimal dynamic strategies in 0.01s achieving 97.8% of DP optimal utility and handles larger problems where DP fails.
An a posteriori framework implemented in PyMHD estimates numerical dissipation in Alfvénic, dynamo, and MRI-driven MHD turbulence, showing it has distinct spectral and anisotropic properties from physical dissipation.
King functions for shifted Gaussians are shown to satisfy a differential equation unitarily equivalent to the radial Schrödinger operator and to form a dense system in radial velocity space.
Information Field Theory is presented as a framework for full-information reconstruction and near-field interferometry of air-shower radio emission.
citing papers explorer
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CEO-Bench: Can Agents Play the Long Game?
Only two of ten advanced AI agents finish a 500-day simulated CEO challenge above the starting cash, and none surpass a hand-tuned rule-based baseline.
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When, why, and how do diffusion posterior samplers fail? A finite-sample lens
A finite-sample perspective reveals that inexact likelihood approximations cause under- or over-estimation of posterior spread at intermediate timesteps, leading to early-stopping sensitivity, mode weighting errors, and hallucinations even from multimodal priors alone.
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Splitting schemes and estimators for stochastic differential equations with H\"older multiplicative noise
Introduces Lie-Trotter and Strang splitting schemes for explicit pseudo-likelihood MLEs in SDEs with Hölder multiplicative noise, proving strong mean-square convergence, state preservation, consistency, and asymptotic normality of the LT estimator.
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Where Does MEV Really Come From? Revisiting CEXDEX Arbitrage on Ethereum
A new discrete-time AMM model with diffusive plus jump price processes shows CEX-DEX arbitrage requires volumes comparable to major liquidity pools and produces profits on the scale of total MEV.
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NATPS: Nonadiabatic Transition Path Sampling Using Time-Reversible MASH Dynamics
NATPS applies time-reversible MASH dynamics within the transition path sampling framework to efficiently generate ensembles of nonadiabatic reactive trajectories on a model system of coupled potential energy surfaces.
-
BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion
BeyondMimic combines compact motion tracking with a unified guided latent diffusion model to master diverse agile behaviors from human demos and solve unseen downstream tasks via test-time classifier guidance.
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Heat-Kernel Entropy Profiles and Geometric Effective Sample Size for Weighted Measures on Manifolds
Heat-kernel smoothing over weighted points on a compact manifold yields a scale-dependent geometric effective sample size that discounts nearby and duplicate particles.
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Relational Multi-Agent Reinforcement Learning for Dynamic Pricing in High-Speed Railway Markets
An entity-graph MARL framework (RACHE) using R-GCN message passing and attention pooling over train-service nodes outperforms baseline algorithms in railway pricing revenue across two simulated market scenarios.
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A Meta Reinforcement Learning Approach to Goals-Based Wealth Management
MetaRL pre-trained on GBWM problems delivers near-optimal dynamic strategies in 0.01s achieving 97.8% of DP optimal utility and handles larger problems where DP fails.
-
Characterization of Numerical Dissipation in Simulations of Magnetohydrodynamic Turbulence
An a posteriori framework implemented in PyMHD estimates numerical dissipation in Alfvénic, dynamo, and MRI-driven MHD turbulence, showing it has distinct spectral and anisotropic properties from physical dissipation.
-
King Function for Shifted Gaussian: Laguerre Structure, Spectral Theory and Density
King functions for shifted Gaussians are shown to satisfy a differential equation unitarily equivalent to the radial Schrödinger operator and to form a dense system in radial velocity space.
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Interferometric Analysis of Air-shower Radio Emission in the Near Field with an Information Field Theory Approach
Information Field Theory is presented as a framework for full-information reconstruction and near-field interferometry of air-shower radio emission.