$Cover Image$

Enhancing Math Reasoning in Small-sized LLMs via Preview Difficulty-Aware Intervention

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Di, Xinhan, JoyJiaoW
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RADAR: Reasoning-Ability and Difficulty-Aware Routing for Reasoning LLMs
by: Fernandez, Nigel, et al.
Published: (2025)

MindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time
by: Kang, Jikun, et al.
Published: (2024)

Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search
by: Li, Shuangtao, et al.
Published: (2025)

MathMixup: Boosting LLM Mathematical Reasoning with Difficulty-Controllable Data Synthesis and Curriculum Learning
by: Li, Xuchen, et al.
Published: (2026)

Light-IF: Endowing LLMs with Generalizable Reasoning via Preview and Self-Checking for Complex Instruction Following
by: Wang, Chenyang, et al.
Published: (2025)

Towards Intrinsic Self-Correction Enhancement in Monte Carlo Tree Search Boosted Reasoning via Iterative Preference Learning
by: Jiang, Huchen, et al.
Published: (2024)

Adaptive Multi-Expert Reasoning via Difficulty-Aware Routing and Uncertainty-Guided Aggregation
by: Ehab, Mohamed, et al.
Published: (2026)

DAG-Math: Graph-of-Thought Guided Mathematical Reasoning in LLMs
by: Zhang, Yuanhe, et al.
Published: (2025)

Reasoning Steps as Curriculum: Using Depth of Thought as a Difficulty Signal for Tuning LLMs
by: Jung, Jeesu, et al.
Published: (2025)

Can LLMs $\textit{understand}$ Math? -- Exploring the Pitfalls in Mathematical Reasoning
by: Roy, Tiasa Singha, et al.
Published: (2025)

WirelessMathLM: Teaching Mathematical Reasoning for LLMs in Wireless Communications with Reinforcement Learning
by: Li, Xin, et al.
Published: (2025)

Compress the Easy, Explore the Hard: Difficulty-Aware Entropy Regularization for Efficient LLM Reasoning
by: Luo, Qin-Wen, et al.
Published: (2026)

†DAGGER: Distractor-Aware Graph Generation for Executable Reasoning in Math Problems
by: Nazi, Zabir Al, et al.
Published: (2026)

An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
by: Chen, Zui, et al.
Published: (2024)

ABench-Physics: Benchmarking Physical Reasoning in LLMs via High-Difficulty and Dynamic Physics Problems
by: Zhang, Yiming, et al.
Published: (2025)

RAST: Reasoning Activation in LLMs via Small-model Transfer
by: Ouyang, Siru, et al.
Published: (2025)

Improving Chain-of-Thought for Logical Reasoning via Attention-Aware Intervention
by: Phuong, Nguyen Minh, et al.
Published: (2026)

Making Small Language Models Efficient Reasoners: Intervention, Supervision, Reinforcement
by: Zhang, Xuechen, et al.
Published: (2025)

Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
by: Feng, Shengyu, et al.
Published: (2024)

A Lean Dataset for International Math Olympiad: Small Steps towards Writing Math Proofs for Hard Problems
by: Yousefzadeh, Roozbeh, et al.
Published: (2024)

MathConstraint: Automated Generation of Verified Combinatorial Reasoning Instances for LLMs
by: Pati, Viresh, et al.
Published: (2026)

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
by: Huang, Kaixuan, et al.
Published: (2025)

GanitLLM: Difficulty-Aware Bengali Mathematical Reasoning through Curriculum-GRPO
by: Dipta, Shubhashis Roy, et al.
Published: (2026)

Which Data Attributes Stimulate Math and Code Reasoning? An Investigation via Influence Functions
by: Kou, Siqi, et al.
Published: (2025)

Understanding the Difficulty of Low-Precision Post-Training Quantization for LLMs
by: Xu, Zifei, et al.
Published: (2024)

Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
by: Zhu, Yuchen, et al.
Published: (2025)

StreetMath: Study of LLMs' Approximation Behaviors
by: Tseng, Chiung-Yi, et al.
Published: (2025)

CER: Confidence Enhanced Reasoning in LLMs
by: Razghandi, Ali, et al.
Published: (2025)

Mitigating Overthinking in Large Reasoning Models via Difficulty-aware Reinforcement Learning
by: Wan, Qian, et al.
Published: (2026)

MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
by: Li, Chengpeng, et al.
Published: (2023)

Simple Vision-Language Math Reasoning via Rendered Text
by: Skripkin, Matvey, et al.
Published: (2025)

AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling
by: Liu, Zihan, et al.
Published: (2024)

PARAMANU-GANITA: Can Small Math Language Models Rival with Large Language Models on Mathematical Reasoning?
by: Niyogi, Mitodru, et al.
Published: (2024)

Optimizing Reasoning Efficiency through Prompt Difficulty Prediction
by: Zhao, Bo, et al.
Published: (2025)

Shorter but not Worse: Frugal Reasoning via Easy Samples as Length Regularizers in Math RLVR
by: Bounhar, Abdelaziz, et al.
Published: (2025)

Calibration-Aware Policy Optimization for Reasoning LLMs
by: Wang, Ziqi, et al.
Published: (2026)

Benchmarking Large Language Models for Math Reasoning Tasks
by: Seßler, Kathrin, et al.
Published: (2024)

Think Smart, Not Hard: Difficulty Adaptive Reasoning for Large Audio Language Models
by: Sheng, Zhichao, et al.
Published: (2025)

Teaching LLMs for Step-Level Automatic Math Correction via Reinforcement Learning
by: Li, Junsong, et al.
Published: (2025)

Unlocking Data Value in Finance: A Study on Distillation and Difficulty-Aware Training
by: Cao, Chuxue, et al.
Published: (2026)