Stochastic AI

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ReCache: Learning Budget-Aware Caching Schedules for Diffusion Models via REINFORCE

 🎲Bayesian Inference  Content type: Academic
arxiv.org·

Hidden Consensus:Preference-Validity Compression in Human Feedback

 📻Noise Engineering  Content type: Academic
arxiv.org·

Overcoming Rank Collapse in Feedback Alignment

 📻Noise Engineering  Content type: Academic
arxiv.org·

RadioDiff-Inv2: Differentiable Diffusion Inversion under Location Drift from Sparse Noisy Measurements for Radio Map Estimation

 🎲Bayesian Inference  Content type: Academic
arxiv.org·

What Do People Actually Want From AI? Mapping Preference Plurality

 🎲Bayesian Inference  Content type: Academic
arxiv.org·

Substrate Asymmetry in User-Side Memory: A Diagnostic Framework

 📻Noise Engineering  Content type: Academic
arxiv.org·

Predicting Physical and Physical-Chemical Properties of Molecular-Based Materials Using Computational Neural Networks

 🌊Analog Computing  Content type: Academic
arxiv.org·

Pretraining Recurrent Networks without Recurrence

 🌊Analog Computing  Content type: Academic
arxiv.org·

Hybridizing Equilibrium Propagation with Ising Machines for Efficient Energy-Based Learning

 Thermodynamic computing  Content type: Academic
arxiv.org·

Synthetic Benchmarks Overstate Forward-Forward Scaling: Real-Data Limits of Layer-Local Training

 📻Noise Engineering  Content type: Academic
arxiv.org·

Reinforcement Learning for Flow-Matching Policies with Density Transport

 Thermodynamic computing  Content type: Academic
arxiv.org·

Perturbative Contrastive Physical Learning

 📻Noise Engineering  Content type: Academic
arxiv.org·

Need We Teach Foundation Models What is a Generative Image? Gradient-Free Generative Artifact Detection via Analytic Spectral Adaptation

 🎲Bayesian Inference  Content type: Academic
arxiv.org·

Business World Model

 🕸️Complex Systems  Content type: Academic
arxiv.org·

Q-VGM: Q-Guided Value-Gradient Matching for Flow-Matching VLA Policies

 📻Noise Engineering  Content type: Academic
arxiv.org·

Uncovering Extreme Event Mechanisms for Prediction and Control with Sensitivity-Balanced Projections

 📻Noise Engineering  Content type: Academic
arxiv.org·

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