Cover Image

Beyond Statistical Learning: Exact Learning Is Essential for General Intelligence

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	György, András, Lattimore, Tor, Lazić, Nevena, Szepesvári, Csaba
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

To See the Unseen: on the Generalization Ability of Transformers in Symbolic Reasoning
by: Lazić, Nevena, et al.
Published: (2026)

Frontier LLMs Still Struggle with Simple Reasoning Tasks
by: Malek, Alan, et al.
Published: (2025)

To Believe or Not to Believe Your LLM
by: Yadkori, Yasin Abbasi, et al.
Published: (2024)

A Diffusion Analysis of Policy Gradient for Stochastic Bandits
by: Lattimore, Tor
Published: (2026)

Balancing optimism and pessimism in offline-to-online learning
by: Sentenac, Flore, et al.
Published: (2025)

A Lyapunov Analysis of Softmax Policy Gradient for Stochastic Bandits
by: Lattimore, Tor
Published: (2026)

Bandit Convex Optimisation
by: Lattimore, Tor
Published: (2024)

Refined Detection for Gumbel Watermarking
by: Lattimore, Tor
Published: (2026)

Rethinking the Foundations for Continual Reinforcement Learning
by: Elelimy, Esraa, et al.
Published: (2025)

Trajectory Data Suffices for Statistically Efficient Learning in Offline RL with Linear $q^π$-Realizability and Concentrability
by: Tkachuk, Volodymyr, et al.
Published: (2024)

Mitigating LLM Hallucinations via Conformal Abstention
by: Yadkori, Yasin Abbasi, et al.
Published: (2024)

Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset
by: Galashov, Alexandre, et al.
Published: (2024)

Partition Tree Weighting for Non-Stationary Stochastic Bandits
by: Veness, Joel, et al.
Published: (2025)

Rectifying Regression in Reinforcement Learning
by: Ayoub, Alex, et al.
Published: (2025)

Towards Error Centric Intelligence I, Beyond Observational Learning
by: Thomas, Marcus A.
Published: (2025)

Open-Endedness is Essential for Artificial Superhuman Intelligence
by: Hughes, Edward, et al.
Published: (2024)

Meta-Statistical Learning: Supervised Learning of Statistical Estimators
by: Peyrard, Maxime, et al.
Published: (2025)

The Return of Pseudosciences in Artificial Intelligence: Have Machine Learning and Deep Learning Forgotten Lessons from Statistics and History?
by: Sublime, Jérémie
Published: (2024)

Beyond the Loss Curve: Scaling Laws, Active Learning, and the Limits of Learning from Exact Posteriors
by: Khorasani, Arian, et al.
Published: (2026)

Exact Learning of Arithmetic with Differentiable Agents
by: Papazov, Hristo, et al.
Published: (2025)

Learning with Exact Invariances in Polynomial Time
by: Soleymani, Ashkan, et al.
Published: (2025)

Revisiting Essential and Nonessential Settings of Evidential Deep Learning
by: Chen, Mengyuan, et al.
Published: (2024)

Artificial Generals Intelligence: Mastering Generals.io with Reinforcement Learning
by: Straka, Matej, et al.
Published: (2025)

On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation
by: Huang, Jiawei, et al.
Published: (2023)

Reward Learning from Multiple Feedback Types
by: Metz, Yannick, et al.
Published: (2025)

Learning from Relevant Subgoals in Successful Dialogs using Iterative Training for Task-oriented Dialog Systems
by: Kaiser, Magdalena, et al.
Published: (2024)

Verification of the Implicit World Model in a Generative Model via Adversarial Sequences
by: Balogh, András, et al.
Published: (2026)

Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond
by: Guo, Kehan, et al.
Published: (2025)

Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Data
by: van Remmerden, Jesse, et al.
Published: (2025)

Sharper Guarantees for Misspecified Kernelized Bandit Optimization
by: Maran, Davide, et al.
Published: (2026)

Weighted Contrastive Learning for Anomaly-Aware Time-Series Forecasting
by: Ekstrand, Joel, et al.
Published: (2025)

Learning to Execute Graph Algorithms Exactly with Graph Neural Networks
by: Qharabagh, Muhammad Fetrat, et al.
Published: (2026)

Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective
by: Phan, Hoang, et al.
Published: (2022)

Learning to Reason Efficiently with Discounted Reinforcement Learning
by: Ayoub, Alex, et al.
Published: (2025)

Small Models, Smarter Learning: The Power of Joint Task Training
by: Both, Csaba, et al.
Published: (2025)

Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models
by: Ziani, Abdelhakim, et al.
Published: (2026)

Neural Active Learning Beyond Bandits
by: Ban, Yikun, et al.
Published: (2024)

Raising the Bar in Graph OOD Generalization: Invariant Learning Beyond Explicit Environment Modeling
by: Shen, Xu, et al.
Published: (2025)

Beyond Experience Retrieval: Learning to Generate Utility-Optimized Structured Experience for Frozen LLMs
by: Li, Xuancheng, et al.
Published: (2026)

Personalized Artificial General Intelligence (AGI) via Neuroscience-Inspired Continuous Learning Systems
by: Gupta, Rajeev, et al.
Published: (2025)