$Image de couverture de livre$

Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ye, Tian, Xu, Zicheng, Li, Yuanzhi, Allen-Zhu, Zeyuan
Format:	Preprint
Publié:	2024
Sujets:	Artificial Intelligence Computation and Language Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problems
par: Ye, Tian, et autres
Publié: (2024)

Physics of Language Models: Part 1, Learning Hierarchical Language Structures
par: Allen-Zhu, Zeyuan, et autres
Publié: (2023)

Physics of Language Models: Part 3.2, Knowledge Manipulation
par: Allen-Zhu, Zeyuan, et autres
Publié: (2023)

Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
par: Allen-Zhu, Zeyuan, et autres
Publié: (2023)

Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws
par: Allen-Zhu, Zeyuan, et autres
Publié: (2024)

SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese
par: Xu, Liang, et autres
Publié: (2024)

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
par: Shao, Zhihong, et autres
Publié: (2024)

PCL-Reasoner-V1.5: Advancing Math Reasoning with Offline Reinforcement Learning
par: Lu, Yao, et autres
Publié: (2026)

Orca-Math: Unlocking the potential of SLMs in Grade School Math
par: Mitra, Arindam, et autres
Publié: (2024)

AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling
par: Liu, Zihan, et autres
Publié: (2024)

AgentMath: Empowering Mathematical Reasoning for Large Language Models via Tool-Augmented Agent
par: Luo, Haipeng, et autres
Publié: (2025)

WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
par: Luo, Haipeng, et autres
Publié: (2023)

PARAMANU-GANITA: Can Small Math Language Models Rival with Large Language Models on Mathematical Reasoning?
par: Niyogi, Mitodru, et autres
Publié: (2024)

Reasoning, Code, or Both? How Large Language Models Handle Variations in Math Questions
par: Kutakh, Matthew
Publié: (2026)

TabularMath: Understanding Math Reasoning over Tables with Large Language Models
par: Tian, Shi-Yu, et autres
Publié: (2025)

MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
par: Li, Chengpeng, et autres
Publié: (2023)

To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization
par: Wang, Haozhe, et autres
Publié: (2025)

Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models -- The Story Goes On
par: Zeng, Liang, et autres
Publié: (2024)

A Careful Examination of Large Language Model Performance on Grade School Arithmetic
par: Zhang, Hugh, et autres
Publié: (2024)

AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning
par: Chen, Yang, et autres
Publié: (2025)

AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset
par: Moshkov, Ivan, et autres
Publié: (2025)

AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL Synergy
par: Liu, Zihan, et autres
Publié: (2025)

Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
par: Albalak, Alon, et autres
Publié: (2025)

Unlocking Multimodal Mathematical Reasoning via Process Reward Model
par: Luo, Ruilin, et autres
Publié: (2025)

MathScale: Scaling Instruction Tuning for Mathematical Reasoning
par: Tang, Zhengyang, et autres
Publié: (2024)

Self-Consistency Boosts Calibration for Math Reasoning
par: Wang, Ante, et autres
Publié: (2024)

Efficient Reasoning with Hidden Thinking
par: Shen, Xuan, et autres
Publié: (2025)

ControlMath: Controllable Data Generation Promotes Math Generalist Models
par: Chen, Nuo, et autres
Publié: (2024)

CriticBench: Benchmarking LLMs for Critique-Correct Reasoning
par: Lin, Zicheng, et autres
Publié: (2024)

Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?
par: Yan, Kai, et autres
Publié: (2025)

An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
par: Chen, Zui, et autres
Publié: (2024)

OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
par: Toshniwal, Shubham, et autres
Publié: (2024)

Offline Learning and Forgetting for Reasoning with Large Language Models
par: Ni, Tianwei, et autres
Publié: (2025)

Math Neurosurgery: Isolating Language Models' Math Reasoning Abilities Using Only Forward Passes
par: Christ, Bryan R., et autres
Publié: (2024)

BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning
par: Zhong, Han, et autres
Publié: (2025)

Generative Evaluation of Complex Reasoning in Large Language Models
par: Lin, Haowei, et autres
Publié: (2025)

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models
par: Xu, Yinggan, et autres
Publié: (2025)

Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
par: Chen, Haolin, et autres
Publié: (2024)

MegaMath: Pushing the Limits of Open Math Corpora
par: Zhou, Fan, et autres
Publié: (2025)

DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning
par: Shao, Zhihong, et autres
Publié: (2025)