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

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

AI Events · 4 min ·
Llms

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...

Reddit - Artificial Intelligence · 1 min ·
Llms

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...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2511.20888] Deep Learning as a Convex Paradigm of Computation: Minimizing Circuit Size with ResNets
Machine Learning

[2511.20888] Deep Learning as a Convex Paradigm of Computation: Minimizing Circuit Size with ResNets

Abstract page for arXiv paper 2511.20888: Deep Learning as a Convex Paradigm of Computation: Minimizing Circuit Size with ResNets

arXiv - Machine Learning · 4 min ·
[2510.12728] Data-Prompt Co-Evolution: Growing Test Sets to Refine LLM Behavior
Llms

[2510.12728] Data-Prompt Co-Evolution: Growing Test Sets to Refine LLM Behavior

Abstract page for arXiv paper 2510.12728: Data-Prompt Co-Evolution: Growing Test Sets to Refine LLM Behavior

arXiv - Machine Learning · 4 min ·
[2510.10223] You only need 4 extra tokens: Synergistic Test-time Adaptation for LLMs
Llms

[2510.10223] You only need 4 extra tokens: Synergistic Test-time Adaptation for LLMs

Abstract page for arXiv paper 2510.10223: You only need 4 extra tokens: Synergistic Test-time Adaptation for LLMs

arXiv - Machine Learning · 4 min ·
[2510.04607] From Imperative to Declarative: Towards LLM-friendly OS Interfaces for Boosted Computer-Use Agents
Llms

[2510.04607] From Imperative to Declarative: Towards LLM-friendly OS Interfaces for Boosted Computer-Use Agents

Abstract page for arXiv paper 2510.04607: From Imperative to Declarative: Towards LLM-friendly OS Interfaces for Boosted Computer-Use Agents

arXiv - Machine Learning · 4 min ·
[2508.02046] NaviMaster: Learning a Unified Policy for GUI and Embodied Navigation Tasks
Machine Learning

[2508.02046] NaviMaster: Learning a Unified Policy for GUI and Embodied Navigation Tasks

Abstract page for arXiv paper 2508.02046: NaviMaster: Learning a Unified Policy for GUI and Embodied Navigation Tasks

arXiv - Machine Learning · 4 min ·
[2507.00629] Generalization performance of narrow one-hidden layer networks in the teacher-student setting
Machine Learning

[2507.00629] Generalization performance of narrow one-hidden layer networks in the teacher-student setting

Abstract page for arXiv paper 2507.00629: Generalization performance of narrow one-hidden layer networks in the teacher-student setting

arXiv - Machine Learning · 4 min ·
[2506.20334] Recurrent neural network-based robust control systems with regional properties and application to MPC design
Machine Learning

[2506.20334] Recurrent neural network-based robust control systems with regional properties and application to MPC design

Abstract page for arXiv paper 2506.20334: Recurrent neural network-based robust control systems with regional properties and application ...

arXiv - Machine Learning · 4 min ·
[2505.20714] Wideband RF Radiance Field Modeling Using Frequency-embedded 3D Gaussian Splatting
Machine Learning

[2505.20714] Wideband RF Radiance Field Modeling Using Frequency-embedded 3D Gaussian Splatting

Abstract page for arXiv paper 2505.20714: Wideband RF Radiance Field Modeling Using Frequency-embedded 3D Gaussian Splatting

arXiv - Machine Learning · 4 min ·
[2504.03486] Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej
Machine Learning

[2504.03486] Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej

Abstract page for arXiv paper 2504.03486: Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDas...

arXiv - Machine Learning · 4 min ·
[2502.02861] Algorithms with Calibrated Machine Learning Predictions
Machine Learning

[2502.02861] Algorithms with Calibrated Machine Learning Predictions

Abstract page for arXiv paper 2502.02861: Algorithms with Calibrated Machine Learning Predictions

arXiv - Machine Learning · 4 min ·
[2502.01754] Evaluation of Large Language Models via Coupled Token Generation
Llms

[2502.01754] Evaluation of Large Language Models via Coupled Token Generation

Abstract page for arXiv paper 2502.01754: Evaluation of Large Language Models via Coupled Token Generation

arXiv - Machine Learning · 4 min ·
[2411.15087] Phrase-Instance Alignment for Generalized Referring Segmentation
Machine Learning

[2411.15087] Phrase-Instance Alignment for Generalized Referring Segmentation

Abstract page for arXiv paper 2411.15087: Phrase-Instance Alignment for Generalized Referring Segmentation

arXiv - Machine Learning · 3 min ·
[2408.03404] Set2Seq Transformer: Temporal and Position-Aware Set Representations for Sequential Multiple-Instance Learning
Machine Learning

[2408.03404] Set2Seq Transformer: Temporal and Position-Aware Set Representations for Sequential Multiple-Instance Learning

Abstract page for arXiv paper 2408.03404: Set2Seq Transformer: Temporal and Position-Aware Set Representations for Sequential Multiple-In...

arXiv - Machine Learning · 4 min ·
[2404.04265] Accelerating Matrix Factorization by Dynamic Pruning for Fast Recommendation
Machine Learning

[2404.04265] Accelerating Matrix Factorization by Dynamic Pruning for Fast Recommendation

Abstract page for arXiv paper 2404.04265: Accelerating Matrix Factorization by Dynamic Pruning for Fast Recommendation

arXiv - Machine Learning · 4 min ·
[2402.08151] Perturbative adaptive importance sampling for Bayesian LOO cross-validation
Machine Learning

[2402.08151] Perturbative adaptive importance sampling for Bayesian LOO cross-validation

Abstract page for arXiv paper 2402.08151: Perturbative adaptive importance sampling for Bayesian LOO cross-validation

arXiv - Machine Learning · 4 min ·
[2312.00357] A Generalizable Deep Learning System for Cardiac MRI
Machine Learning

[2312.00357] A Generalizable Deep Learning System for Cardiac MRI

Abstract page for arXiv paper 2312.00357: A Generalizable Deep Learning System for Cardiac MRI

arXiv - Machine Learning · 4 min ·
[2603.13334] Lipschitz-Based Robustness Certification Under Floating-Point Execution
Machine Learning

[2603.13334] Lipschitz-Based Robustness Certification Under Floating-Point Execution

Abstract page for arXiv paper 2603.13334: Lipschitz-Based Robustness Certification Under Floating-Point Execution

arXiv - Machine Learning · 4 min ·
[2603.16661] Self-Aware Markov Models for Discrete Reasoning
Machine Learning

[2603.16661] Self-Aware Markov Models for Discrete Reasoning

Abstract page for arXiv paper 2603.16661: Self-Aware Markov Models for Discrete Reasoning

arXiv - Machine Learning · 4 min ·
[2603.13909] FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for Non-IID Data
Machine Learning

[2603.13909] FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for Non-IID Data

Abstract page for arXiv paper 2603.13909: FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for...

arXiv - Machine Learning · 4 min ·
[2511.16148] Enhancing Nuclear Reactor Core Simulation through Data-Based Surrogate Models
Machine Learning

[2511.16148] Enhancing Nuclear Reactor Core Simulation through Data-Based Surrogate Models

Abstract page for arXiv paper 2511.16148: Enhancing Nuclear Reactor Core Simulation through Data-Based Surrogate Models

arXiv - Machine Learning · 3 min ·
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