Machine Learning

Hub Group Using AI, Machine Learning for Real-Time Visibility of Shipments

Von Hammerstein’s Ghost: What a Prussian General’s Officer Typology Can Teach Us About AI Misalignment

Greetings all - I've posted mostly in r/claudecode and r/aigamedev a couple of times previously. Working with CC for personal projects re...

World models will be the next big thing, bye-bye LLMs

Was at Nvidia's GTC conference recently and honestly, it was one of the most eye-opening events I've attended in a while. There was a lot...

[2601.16399] A Hessian-Free Actor-Critic Algorithm for Bi-Level Reinforcement Learning with Applications to LLM Fine-Tuning

Abstract page for arXiv paper 2601.16399: A Hessian-Free Actor-Critic Algorithm for Bi-Level Reinforcement Learning with Applications to ...

[2601.00473] Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning

Abstract page for arXiv paper 2601.00473: Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning

[2511.18789] Perturbing the Derivative: Doubly Wild Refitting for Model-Free Evaluation of Opaque Machine Learning Predictors

Abstract page for arXiv paper 2511.18789: Perturbing the Derivative: Doubly Wild Refitting for Model-Free Evaluation of Opaque Machine Le...

[2511.18000] Reward Engineering for Spatial Epidemic Simulations: A Reinforcement Learning Platform for Individual Behavioral Learning

Abstract page for arXiv paper 2511.18000: Reward Engineering for Spatial Epidemic Simulations: A Reinforcement Learning Platform for Indi...

[2512.03923] Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations

Abstract page for arXiv paper 2512.03923: Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations

[2511.18178] Bayesian Calibration of Engine-out NOx Models for Engine-to-Engine Transferability

Abstract page for arXiv paper 2511.18178: Bayesian Calibration of Engine-out NOx Models for Engine-to-Engine Transferability

[2511.11743] Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts

Abstract page for arXiv paper 2511.11743: Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts

[2511.06767] QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common Patterns in Nonlinear Operations

Abstract page for arXiv paper 2511.06767: QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common P...

[2510.27321] MedM2T: A MultiModal Framework for Time-Aware Modeling with Electronic Health Record and Electrocardiogram Data

Abstract page for arXiv paper 2510.27321: MedM2T: A MultiModal Framework for Time-Aware Modeling with Electronic Health Record and Electr...

[2510.14814] Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift

Abstract page for arXiv paper 2510.14814: Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift

[2510.15495] OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning

Abstract page for arXiv paper 2510.15495: OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning

[2510.14751] Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries

Abstract page for arXiv paper 2510.14751: Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries

[2510.06020] RamPINN: Recovering Raman Spectra From Coherent Anti-Stokes Spectra Using Embedded Physics

Abstract page for arXiv paper 2510.06020: RamPINN: Recovering Raman Spectra From Coherent Anti-Stokes Spectra Using Embedded Physics

[2510.00430] PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment

Abstract page for arXiv paper 2510.00430: PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment

[2510.01169] Fiaingen: A financial time series generative method matching real-world data quality

Abstract page for arXiv paper 2510.01169: Fiaingen: A financial time series generative method matching real-world data quality

[2509.24140] A signal separation view of classification

Abstract page for arXiv paper 2509.24140: A signal separation view of classification

[2508.17381] DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning

Abstract page for arXiv paper 2508.17381: DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning

[2508.02330] A Compression Based Classification Framework Using Symbolic Dynamics of Chaotic Maps

Abstract page for arXiv paper 2508.02330: A Compression Based Classification Framework Using Symbolic Dynamics of Chaotic Maps

[2507.21037] When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject Motor Imagery Decoding

Abstract page for arXiv paper 2507.21037: When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject ...

[2507.07580] COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation

Abstract page for arXiv paper 2507.07580: COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation