Verification with Transfer: Exact Information Frontiers and Their Price in Calls
cs.LG, cs.CR, cs.IT, math.IT, stat.ML
Submitted: 2026-10-08
Updated: 2026-10-08
Terminology
Sources
- What learning algorithm is in-context learning? Investigations with linear models
- Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit
- When Is Compositional Reasoning Learnable from Verifiable Rewards?
- Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
- Evaluating Large Language Models Trained on Code
- Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective
- What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
- On the Emergence of Implicit Curriculum in RLVR Learning Dynamics
- Near-optimal Nonmyopic Value of Information in Graphical Models
- Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
- The Expressive Power of Transformers with Chain of Thought
- Learning to Reason with Curriculum II: Compositional Generalization
- Outcome-Based RL Provably Leads Transformers to Reason, but Only With the Right Data
- Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression
- Non-Asymptotic Fundamental Limits of Guessing Subject to Distortion
- An algorithm for computing generalized Hamming weights and the Sage package GHWs
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- RL's Razor: Why Online Reinforcement Learning Forgets Less
- A Relative-Budget Theory for Reinforcement Learning with Verifiable Rewards in Large Language Model Reasoning
- Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks