Cover Image

Learning to Correct: Calibrated Reinforcement Learning for Multi-Attempt Chain-of-Thought

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ildiz, Muhammed Emrullah, Gozeten, Halil Alperen, Taga, Ege Onur, Oymak, Samet
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data
by: Taga, Ege Onur, et al.
Published: (2025)

Retrieval Augmented Time Series Forecasting
by: Tire, Kutay, et al.
Published: (2024)

High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws
by: Ildiz, M. Emrullah, et al.
Published: (2024)

Evolutionary Multi-Task Optimization for LLM-Guided Program Discovery
by: Gozeten, Halil Alperen, et al.
Published: (2026)

Continuous Chain of Thought Enables Parallel Exploration and Reasoning
by: Gozeten, Halil Alperen, et al.
Published: (2025)

Test-Time Training Provably Improves Transformers as In-context Learners
by: Gozeten, Halil Alperen, et al.
Published: (2025)

Learning to Bet for Horizon-Aware Anytime-Valid Testing
by: Taga, Ege Onur, et al.
Published: (2026)

Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning
by: Zhang, Xuechen, et al.
Published: (2024)

From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers
by: Ildiz, M. Emrullah, et al.
Published: (2024)

Mechanics of Next Token Prediction with Self-Attention
by: Li, Yingcong, et al.
Published: (2024)

Covariance-Aware Transformers for Quadratic Programming and Decision Making
by: Tire, Kutay, et al.
Published: (2026)

In-Context Learning Under Regime Change
by: Dudley, Carson, et al.
Published: (2026)

Latent Chain-of-Thought Improves Structured-Data Transformers
by: Dudley, Carson, et al.
Published: (2026)

Can Transformers Learn Optimal Filtering for Unknown Systems?
by: Balim, Haldun, et al.
Published: (2023)

Thresholded Lexicographic Ordered Multiobjective Reinforcement Learning
by: Tercan, Alperen, et al.
Published: (2024)

Learning from Failures in Multi-Attempt Reinforcement Learning
by: Chung, Stephen, et al.
Published: (2025)

In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
by: Huang, Sili, et al.
Published: (2024)

Identifying Trustworthiness Challenges in Deep Learning Models for Continental-Scale Water Quality Prediction
by: Xia, Xiaobo, et al.
Published: (2025)

Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
by: Li, Yingcong, et al.
Published: (2024)

Transformers Learn to Implement Multi-step Gradient Descent with Chain of Thought
by: Huang, Jianhao, et al.
Published: (2025)

AdaCoT: Pareto-Optimal Adaptive Chain-of-Thought Triggering via Reinforcement Learning
by: Lou, Chenwei, et al.
Published: (2025)

Mitigating Participation Imbalance Bias in Asynchronous Federated Learning
by: Chang, Xiangyu, et al.
Published: (2025)

Gating is Weighting: Understanding Gated Linear Attention through In-context Learning
by: Li, Yingcong, et al.
Published: (2025)

Reinforcement Learning for Chain of Thought Compression with One-Domain-to-All Generalization
by: Li, Hanyu, et al.
Published: (2025)

When and How Unlabeled Data Provably Improve In-Context Learning
by: Li, Yingcong, et al.
Published: (2025)

Reinforcing Chain-of-Thought Reasoning with Self-Evolving Rubrics
by: Sheng, Leheng, et al.
Published: (2026)

Transformers as Support Vector Machines
by: Tarzanagh, Davoud Ataee, et al.
Published: (2023)

The Kinetics of Reasoning: How Chain-of-Thought Shapes Learning in Transformers?
by: Pengmei, Zihan, et al.
Published: (2025)

A Theory of Learning with Autoregressive Chain of Thought
by: Joshi, Nirmit, et al.
Published: (2025)

SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG
by: Zhang, Xuechen, et al.
Published: (2025)

Multi-Step Likelihood-Ratio Correction for Reinforcement Learning with Verifiable Rewards
by: Yoon, Deokgyu, et al.
Published: (2026)

Learning from Partial Chain-of-Thought via Truncated-Reasoning Self-Distillation
by: Silvestri, Gianluigi, et al.
Published: (2026)

Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification Algorithms
by: Dagdanov, Resul, et al.
Published: (2022)

Learning to Clean: Reinforcement Learning for Noisy Label Correction
by: Heidari, Marzi, et al.
Published: (2025)

ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback
by: Byun, Ju-Seung, et al.
Published: (2024)

Demystifying Chains, Trees, and Graphs of Thoughts
by: Besta, Maciej, et al.
Published: (2024)

Think Consistently, Reason Efficiently: Energy-Based Calibration for Implicit Chain-of-Thought
by: Chen, Zhikang, et al.
Published: (2025)

Curriculum Learning for Efficient Chain-of-Thought Distillation via Structure-Aware Masking and GRPO
by: Yu, Bowen, et al.
Published: (2026)

GLaDiGAtor: Language-Model-Augmented Multi-Relation Graph Learning for Predicting Disease-Gene Associations
by: Kuzucu, Osman Onur, et al.
Published: (2026)

Mitigating LLM Hallucination via Behaviorally Calibrated Reinforcement Learning
by: Wu, Jiayun, et al.
Published: (2025)