Cover Image

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yeh, Cheng-Kai, Lee, Hsing-Wang, Kuo, Chung-Hung, Huang, Hen-Hsen
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Large Language Model Pruning
by: Huang, Hanjuan, et al.
Published: (2024)

Unveiling Selection Biases: Exploring Order and Token Sensitivity in Large Language Models
by: Wei, Sheng-Lun, et al.
Published: (2024)

Diverge to Induce Prompting: Multi-Rationale Induction for Zero-Shot Reasoning
by: Chen, Po-Chun, et al.
Published: (2026)

Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search
by: Liu, Max, et al.
Published: (2024)

Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning
by: Liu, Qihao, et al.
Published: (2025)

Adversarial Reinforcement Learning for Large Language Model Agent Safety
by: Wang, Zizhao, et al.
Published: (2025)

Strategy-Induct: Task-Level Strategy Induction for Instruction Generation
by: Chen, Po-Chun, et al.
Published: (2026)

Reinforcement Learning for Reasoning in Large Language Models with One Training Example
by: Wang, Yiping, et al.
Published: (2025)

Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
by: Xi, Zhiheng, et al.
Published: (2024)

Revisiting Entropy in Reinforcement Learning for Large Reasoning Models
by: Jin, Renren, et al.
Published: (2025)

Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses
by: Su, Hung-Ting, et al.
Published: (2024)

The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models
by: Cui, Ganqu, et al.
Published: (2025)

A Survey of Reinforcement Learning for Large Reasoning Models
by: Zhang, Kaiyan, et al.
Published: (2025)

DISPO: Enhancing Training Efficiency and Stability in Reinforcement Learning for Large Language Model Mathematical Reasoning
by: Karaman, Batuhan K., et al.
Published: (2026)

A Relative-Budget Theory for Reinforcement Learning with Verifiable Rewards in Large Language Model Reasoning
by: Wachi, Akifumi, et al.
Published: (2026)

Do Before You Judge: Self-Reference as a Pathway to Better LLM Evaluation
by: Lin, Wei-Hsiang, et al.
Published: (2025)

Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance
by: Xiong, Kai, et al.
Published: (2024)

Revisiting Uncertainty Estimation and Calibration of Large Language Models
by: Tao, Linwei, et al.
Published: (2025)

Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts
by: Pang, Jing-Cheng, et al.
Published: (2024)

Offline Learning and Forgetting for Reasoning with Large Language Models
by: Ni, Tianwei, et al.
Published: (2025)

Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models
by: Yang, Yukang, et al.
Published: (2025)

On Calibration of Large Language Models: From Response To Capability
by: Yang, Sin-Han, et al.
Published: (2026)

Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
by: Deng, Yihe, et al.
Published: (2025)

DivLogicEval: A Framework for Benchmarking Logical Reasoning Evaluation in Large Language Models
by: Chung, Tsz Ting, et al.
Published: (2025)

CARE-RFT: Confidence-Anchored Reinforcement Finetuning for Reliable Reasoning in Large Language Models
by: Li, Shuozhe, et al.
Published: (2026)

The Model Agreed, But Didn't Learn: Diagnosing Surface Compliance in Large Language Models
by: Gu, Xiaojie, et al.
Published: (2026)

Think Before You Prune: Self-Reflective Structured Pruning for Reasoning Language Models
by: Wang, Ziyan, et al.
Published: (2025)

CausalARC: Abstract Reasoning with Causal World Models
by: Maasch, Jacqueline, et al.
Published: (2025)

WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
by: Luo, Haipeng, et al.
Published: (2023)

Democratizing LLM Efficiency: From Hyperscale Optimizations to Universal Deployability
by: Huang, Hen-Hsen
Published: (2025)

Large Language and Reasoning Models are Shallow Disjunctive Reasoners
by: Khalid, Irtaza, et al.
Published: (2025)

Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression
by: Huang, Jiameng, et al.
Published: (2025)

Generative Evaluation of Complex Reasoning in Large Language Models
by: Lin, Haowei, et al.
Published: (2025)

Nemotron-Cascade: Scaling Cascaded Reinforcement Learning for General-Purpose Reasoning Models
by: Wang, Boxin, et al.
Published: (2025)

Exploring the Reversal Curse and Other Deductive Logical Reasoning in BERT and GPT-Based Large Language Models
by: Wu, Da, et al.
Published: (2023)

Large Language Model Reasoning Failures
by: Song, Peiyang, et al.
Published: (2026)

Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods
by: Cao, Yuji, et al.
Published: (2024)

Group-Aware Reinforcement Learning for Output Diversity in Large Language Models
by: Anschel, Oron, et al.
Published: (2025)

Mental Modeling of Reinforcement Learning Agents by Language Models
by: Lu, Wenhao, et al.
Published: (2024)

Combining Induction and Transduction for Abstract Reasoning
by: Li, Wen-Ding, et al.
Published: (2024)