Imagen de Portada

MathDuels: Evaluating LLMs as Problem Posers and Solvers

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Xu, Zhiqiu, Jin, Shibo, Arya, Shreya, Naik, Mayur
Formato:	Preprint
Publicado:	2026
Materias:	Computation and Language Software Engineering
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Solver-Independent Automated Problem Formulation via LLMs for High-Cost Simulation-Driven Design
por: Li, Yuchen, et al.
Publicado: (2025)

Program Structure Aware Precondition Generation
por: Dinella, Elizabeth, et al.
Publicado: (2023)

IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities
por: Li, Ziyang, et al.
Publicado: (2024)

Can LLMs Generate High-Quality Test Cases for Algorithm Problems? TestCase-Eval: A Systematic Evaluation of Fault Coverage and Exposure
por: Yang, Zheyuan, et al.
Publicado: (2025)

Evaluation of Code LLMs on Geospatial Code Generation
por: Gramacki, Piotr, et al.
Publicado: (2024)

Isolating Language-Coding from Problem-Solving: Benchmarking LLMs with PseudoEval
por: Wu, Jiarong, et al.
Publicado: (2025)

QLCoder: A Query Synthesizer For Static Analysis of Security Vulnerabilities
por: Wang, Claire, et al.
Publicado: (2025)

AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions
por: Wang, Zihan, et al.
Publicado: (2025)

FairCoder: Evaluating Social Bias of LLMs in Code Generation
por: Du, Yongkang, et al.
Publicado: (2025)

Showing LLM-Generated Code Selectively Based on Confidence of LLMs
por: Li, Jia, et al.
Publicado: (2024)

CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smells
por: Naik, Atharva, et al.
Publicado: (2024)

SimCT: A Simple Consistency Test Protocol in LLMs Development Lifecycle
por: Zhao, Fufangchen, et al.
Publicado: (2024)

Tool-Aware Planning in Contact Center AI: Evaluating LLMs through Lineage-Guided Query Decomposition
por: Nathan, Varun, et al.
Publicado: (2026)

Rethinking Repetition Problems of LLMs in Code Generation
por: Dong, Yihong, et al.
Publicado: (2025)

From Output to Evaluation: Does Raw Instruction-Tuned Code LLMs Output Suffice for Fill-in-the-Middle Code Generation?
por: Ahmad, Wasi Uddin, et al.
Publicado: (2025)

Type-Aware Retrieval-Augmented Generation with Dependency Closure for Solver-Executable Industrial Optimization Modeling
por: Zhong, Y., et al.
Publicado: (2026)

AutoCode: LLMs as Problem Setters for Competitive Programming
por: Zhou, Shang, et al.
Publicado: (2025)

CodeSpecBench: Benchmarking LLMs for Executable Behavioral Specification Generation
por: Chen, Zaoyu, et al.
Publicado: (2026)

Multi-Programming Language Sandbox for LLMs
por: Dou, Shihan, et al.
Publicado: (2024)

Humanity's Last Code Exam: Can Advanced LLMs Conquer Human's Hardest Code Competition?
por: Li, Xiangyang, et al.
Publicado: (2025)

CodePivot: Bootstrapping Multilingual Transpilation in LLMs via Reinforcement Learning without Parallel Corpora
por: Li, Shangyu, et al.
Publicado: (2026)

Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
por: Wang, Junqiao, et al.
Publicado: (2024)

Code-Vision: Evaluating Multimodal LLMs Logic Understanding and Code Generation Capabilities
por: Wang, Hanbin, et al.
Publicado: (2025)

LLMs in Mobile Apps: Practices, Challenges, and Opportunities
por: Hau, Kimberly, et al.
Publicado: (2025)

EvoCodeBench: An Evolving Code Generation Benchmark with Domain-Specific Evaluations
por: Li, Jia, et al.
Publicado: (2024)

DependEval: Benchmarking LLMs for Repository Dependency Understanding
por: Du, Junjia, et al.
Publicado: (2025)

Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities
por: Khare, Avishree, et al.
Publicado: (2023)

Characterizing and Evaluating the Reliability of LLMs against Jailbreak Attacks
por: Chen, Kexin, et al.
Publicado: (2024)

LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs
por: Xia, Yunhui, et al.
Publicado: (2025)

CodeScout: Contextual Problem Statement Enhancement for Software Agents
por: Suri, Manan, et al.
Publicado: (2026)

NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations
por: Chen, Junkai, et al.
Publicado: (2024)

Model Editing for LLMs4Code: How Far are We?
por: Li, Xiaopeng, et al.
Publicado: (2024)

Coffee: Boost Your Code LLMs by Fixing Bugs with Feedback
por: Moon, Seungjun, et al.
Publicado: (2023)

Evaluate-and-Purify: Fortifying Code Language Models Against Adversarial Attacks Using LLM-as-a-Judge
por: Mu, Wenhan, et al.
Publicado: (2025)

Quality Matters: Evaluating Synthetic Data for Tool-Using LLMs
por: Iskander, Shadi, et al.
Publicado: (2024)

Bias Testing and Mitigation in Black Box LLMs using Metamorphic Relations
por: Salimian, Sina, et al.
Publicado: (2025)

Benchmarking LLMs for Unit Test Generation from Real-World Functions
por: Huang, Dong, et al.
Publicado: (2025)

RITFIS: Robust input testing framework for LLMs-based intelligent software
por: Xiao, Mingxuan, et al.
Publicado: (2024)

ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
por: Zhang, Chenchen, et al.
Publicado: (2025)

Leveraging LLMs for Grammar Adaptation: A Study on Metamodel-Grammar Co-Evolution
por: Zhang, Weixing, et al.
Publicado: (2026)