Machine Learning

International treaty for pausing the development of more powerful AI models

Personally, I think AI is interesting. But I recognize it might be dangerous, especially given the pace of development. Here's my suggest...

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

Sam Altman's Coworkers Say He Can Barely Code and Misunderstands Basic Machine Learning Concepts

[2603.24402] AI-Supervisor: Autonomous AI Research Supervision via a Persistent Research World Model

Abstract page for arXiv paper 2603.24402: AI-Supervisor: Autonomous AI Research Supervision via a Persistent Research World Model

[2603.16951] Minimum-Action Learning: Energy-Constrained Symbolic Model Selection for Physical Law Identification from Noisy Data

Abstract page for arXiv paper 2603.16951: Minimum-Action Learning: Energy-Constrained Symbolic Model Selection for Physical Law Identific...

[2603.23610] Environment Maps: Structured Environmental Representations for Long-Horizon Agents

Abstract page for arXiv paper 2603.23610: Environment Maps: Structured Environmental Representations for Long-Horizon Agents

[2601.21747] Temporal Sepsis Modeling: a Fully Interpretable Relational Way

Abstract page for arXiv paper 2601.21747: Temporal Sepsis Modeling: a Fully Interpretable Relational Way

[2603.08561] RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback

Abstract page for arXiv paper 2603.08561: RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback

[2601.18420] Gradient Regularized Natural Gradients

Abstract page for arXiv paper 2601.18420: Gradient Regularized Natural Gradients

[2511.07436] Analysing Environmental Efficiency in AI for X-Ray Diagnosis

Abstract page for arXiv paper 2511.07436: Analysing Environmental Efficiency in AI for X-Ray Diagnosis

[2601.02856] Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning

Abstract page for arXiv paper 2601.02856: Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning

[2601.00428] Interpretable ML Under the Microscope: Performance, Meta-Features, and the Regression-Classification Predictability Gap

Abstract page for arXiv paper 2601.00428: Interpretable ML Under the Microscope: Performance, Meta-Features, and the Regression-Classific...

[2510.18087] Planned Diffusion

Abstract page for arXiv paper 2510.18087: Planned Diffusion

[2509.23768] From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

Abstract page for arXiv paper 2509.23768: From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

[2512.18951] Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models

Abstract page for arXiv paper 2512.18951: Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models

[2509.03345] Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning

Abstract page for arXiv paper 2509.03345: Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive ...

[2512.10152] Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability

Abstract page for arXiv paper 2512.10152: Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability

[2512.01906] Delays in Spiking Neural Networks: A State Space Model Approach

Abstract page for arXiv paper 2512.01906: Delays in Spiking Neural Networks: A State Space Model Approach

[2504.15780] TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving

Abstract page for arXiv paper 2504.15780: TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving

[2503.03361] Concepts Learned Visually by Infants Can Contribute to Visual Learning and Understanding in AI Models

Abstract page for arXiv paper 2503.03361: Concepts Learned Visually by Infants Can Contribute to Visual Learning and Understanding in AI ...

[2512.01678] Morphling: Fast, Fused, and Flexible GNN Training at Scale

Abstract page for arXiv paper 2512.01678: Morphling: Fast, Fused, and Flexible GNN Training at Scale

[2511.22344] Cleaning the Pool: Progressive Filtering of Unlabeled Pools in Deep Active Learning

Abstract page for arXiv paper 2511.22344: Cleaning the Pool: Progressive Filtering of Unlabeled Pools in Deep Active Learning

[2410.20894] Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots

Abstract page for arXiv paper 2410.20894: Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Deto...