Saved in:
| Main Authors: | Sun, Zhishen, Dai, Guang, Ye, Haishan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.08055 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Numerical Sensitivity and Robustness: Exploring the Flaws of Mathematical Reasoning in Large Language Models
by: Sun, Zhishen, et al.
Published: (2025)
by: Sun, Zhishen, et al.
Published: (2025)
ESSAM: A Novel Competitive Evolution Strategies Approach to Reinforcement Learning for Memory Efficient LLMs Fine-Tuning
by: Sun, Zhishen, et al.
Published: (2026)
by: Sun, Zhishen, et al.
Published: (2026)
Evaluating the Reasoning Abilities of LLMs on Underrepresented Mathematics Competition Problems
by: Golladay, Samuel, et al.
Published: (2025)
by: Golladay, Samuel, et al.
Published: (2025)
From $O(mn)$ to $O(r^2)$: Two-Sided Low-Rank Communication for Adam in Distributed Training with Memory Efficiency
by: Dang, Sizhe, et al.
Published: (2026)
by: Dang, Sizhe, et al.
Published: (2026)
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
by: Singh, Joykirat, et al.
Published: (2024)
by: Singh, Joykirat, et al.
Published: (2024)
Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs
by: Cheng, Kewei, et al.
Published: (2024)
by: Cheng, Kewei, et al.
Published: (2024)
CogMath: Assessing LLMs' Authentic Mathematical Ability from a Human Cognitive Perspective
by: Liu, Jiayu, et al.
Published: (2025)
by: Liu, Jiayu, et al.
Published: (2025)
MAR:Multi-Agent Reflexion Improves Reasoning Abilities in LLMs
by: Ozer, Onat, et al.
Published: (2025)
by: Ozer, Onat, et al.
Published: (2025)
Multilingual Mathematical Reasoning: Advancing Open-Source LLMs in Hindi and English
by: Anand, Avinash, et al.
Published: (2024)
by: Anand, Avinash, et al.
Published: (2024)
FZOO: Fast Zeroth-Order Optimizer for Fine-Tuning Large Language Models towards Adam-Scale Speed
by: Dang, Sizhe, et al.
Published: (2025)
by: Dang, Sizhe, et al.
Published: (2025)
Quantization Meets Reasoning: Exploring and Mitigating Degradation of Low-Bit LLMs in Mathematical Reasoning
by: Li, Zhen, et al.
Published: (2025)
by: Li, Zhen, et al.
Published: (2025)
Improving LLMs' Generalized Reasoning Abilities by Graph Problems
by: Zhang, Qifan, et al.
Published: (2025)
by: Zhang, Qifan, et al.
Published: (2025)
Diversity of Thought Improves Reasoning Abilities of LLMs
by: Naik, Ranjita, et al.
Published: (2023)
by: Naik, Ranjita, et al.
Published: (2023)
RADAR: Reasoning-Ability and Difficulty-Aware Routing for Reasoning LLMs
by: Fernandez, Nigel, et al.
Published: (2025)
by: Fernandez, Nigel, et al.
Published: (2025)
ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints
by: Xu, Rui, et al.
Published: (2025)
by: Xu, Rui, et al.
Published: (2025)
Enhancing Reasoning Abilities of Small LLMs with Cognitive Alignment
by: Cai, Wenrui, et al.
Published: (2025)
by: Cai, Wenrui, et al.
Published: (2025)
Can LLMs Reliably Simulate Real Students' Abilities in Mathematics and Reading Comprehension?
by: Srivatsa, KV Aditya, et al.
Published: (2025)
by: Srivatsa, KV Aditya, et al.
Published: (2025)
Enhancing Mathematical Reasoning in LLMs with Background Operators
by: Chen, Jiajun, et al.
Published: (2024)
by: Chen, Jiajun, et al.
Published: (2024)
Navigating the Labyrinth: Evaluating LLMs' Ability to Reason About Search Problems
by: Borazjanizadeh, Nasim, et al.
Published: (2024)
by: Borazjanizadeh, Nasim, et al.
Published: (2024)
How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities
by: Mo, Lingbo, et al.
Published: (2023)
by: Mo, Lingbo, et al.
Published: (2023)
Reasoning with LLMs for Zero-Shot Vulnerability Detection
by: Zibaeirad, Arastoo, et al.
Published: (2025)
by: Zibaeirad, Arastoo, et al.
Published: (2025)
HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs
by: Ospanov, Azim, et al.
Published: (2025)
by: Ospanov, Azim, et al.
Published: (2025)
Boosting Vulnerability Detection of LLMs via Curriculum Preference Optimization with Synthetic Reasoning Data
by: Wen, Xin-Cheng, et al.
Published: (2025)
by: Wen, Xin-Cheng, et al.
Published: (2025)
Guarded Repair for Harm-Aware Post-hoc Replacement of LLM Mathematical Reasoning
by: Xia, Haizhou
Published: (2026)
by: Xia, Haizhou
Published: (2026)
Embedding Self-Correction as an Inherent Ability in Large Language Models for Enhanced Mathematical Reasoning
by: Gao, Kuofeng, et al.
Published: (2024)
by: Gao, Kuofeng, et al.
Published: (2024)
SAAS: Solving Ability Amplification Strategy for Enhanced Mathematical Reasoning in Large Language Models
by: Kim, Hyeonwoo, et al.
Published: (2024)
by: Kim, Hyeonwoo, et al.
Published: (2024)
Can MLLMs Absorb Math Reasoning Abilities from LLMs as Free Lunch?
by: Hu, Yijie, et al.
Published: (2025)
by: Hu, Yijie, et al.
Published: (2025)
Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring
by: Anand, Avinash, et al.
Published: (2024)
by: Anand, Avinash, et al.
Published: (2024)
Weight Patching: Toward Source-Level Mechanistic Localization in LLMs
by: Sun, Chenghao, et al.
Published: (2026)
by: Sun, Chenghao, et al.
Published: (2026)
QED: An Open-Source Multi-Agent System for Generating Mathematical Proofs on Open Problems
by: An, Chenyang, et al.
Published: (2026)
by: An, Chenyang, et al.
Published: (2026)
Harnessing the Power of LLMs in Source Code Vulnerability Detection
by: Mahyari, Andrew A
Published: (2024)
by: Mahyari, Andrew A
Published: (2024)
EmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robot Collaboration
by: Zeng, Haishan, et al.
Published: (2026)
by: Zeng, Haishan, et al.
Published: (2026)
An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
by: Chen, Zui, et al.
Published: (2024)
by: Chen, Zui, et al.
Published: (2024)
Improving Multi-Step Reasoning Abilities of Large Language Models with Direct Advantage Policy Optimization
by: Liu, Jiacai, et al.
Published: (2024)
by: Liu, Jiacai, et al.
Published: (2024)
Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization
by: Tan, Chengli, et al.
Published: (2025)
by: Tan, Chengli, et al.
Published: (2025)
Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning
by: Wang, Jiayu, et al.
Published: (2025)
by: Wang, Jiayu, et al.
Published: (2025)
ReasonAgain: Using Extractable Symbolic Programs to Evaluate Mathematical Reasoning
by: Yu, Xiaodong, et al.
Published: (2024)
by: Yu, Xiaodong, et al.
Published: (2024)
Tables as Texts or Images: Evaluating the Table Reasoning Ability of LLMs and MLLMs
by: Deng, Naihao, et al.
Published: (2024)
by: Deng, Naihao, et al.
Published: (2024)
Unmasking Reasoning Processes: A Process-aware Benchmark for Evaluating Structural Mathematical Reasoning in LLMs
by: Zheng, Xiang, et al.
Published: (2026)
by: Zheng, Xiang, et al.
Published: (2026)
An Investigation of Robustness of LLMs in Mathematical Reasoning: Benchmarking with Mathematically-Equivalent Transformation of Advanced Mathematical Problems
by: Hao, Yuren, et al.
Published: (2025)
by: Hao, Yuren, et al.
Published: (2025)
Similar Items
-
Numerical Sensitivity and Robustness: Exploring the Flaws of Mathematical Reasoning in Large Language Models
by: Sun, Zhishen, et al.
Published: (2025) -
ESSAM: A Novel Competitive Evolution Strategies Approach to Reinforcement Learning for Memory Efficient LLMs Fine-Tuning
by: Sun, Zhishen, et al.
Published: (2026) -
Evaluating the Reasoning Abilities of LLMs on Underrepresented Mathematics Competition Problems
by: Golladay, Samuel, et al.
Published: (2025) -
From $O(mn)$ to $O(r^2)$: Two-Sided Low-Rank Communication for Adam in Distributed Training with Memory Efficiency
by: Dang, Sizhe, et al.
Published: (2026) -
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
by: Singh, Joykirat, et al.
Published: (2024)