Cover Image

Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Rem, Dai, Julian, Vasilakis, Nikos, Rinard, Martin
Format:	Preprint
Published:	2025
Subjects:	Software Engineering Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models
by: Riddell, Martin, et al.
Published: (2024)

CodeJudge: Evaluating Code Generation with Large Language Models
by: Tong, Weixi, et al.
Published: (2024)

CodeEditorBench: Evaluating Code Editing Capability of Large Language Models
by: Guo, Jiawei, et al.
Published: (2024)

TAROT: Test-driven and Capability-adaptive Curriculum Reinforcement Fine-tuning for Code Generation with Large Language Models
by: Park, Chansung, et al.
Published: (2026)

Evaluating Language Models for Efficient Code Generation
by: Liu, Jiawei, et al.
Published: (2024)

Evaluating the Formal Reasoning Capabilities of Large Language Models through Chomsky Hierarchy
by: Dong, Yihong, et al.
Published: (2026)

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
by: Jain, Naman, et al.
Published: (2024)

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
by: Weyssow, Martin, et al.
Published: (2023)

NExT: Teaching Large Language Models to Reason about Code Execution
by: Ni, Ansong, et al.
Published: (2024)

CodeUltraFeedback: An LLM-as-a-Judge Dataset for Aligning Large Language Models to Coding Preferences
by: Weyssow, Martin, et al.
Published: (2024)

CodeVisionary: An Agent-based Framework for Evaluating Large Language Models in Code Generation
by: Wang, Xinchen, et al.
Published: (2025)

Prompting and Fine-tuning Large Language Models for Automated Code Review Comment Generation
by: Haider, Md. Asif, et al.
Published: (2024)

GLLM: Self-Corrective G-Code Generation using Large Language Models with User Feedback
by: Abdelaal, Mohamed, et al.
Published: (2025)

Optimizing Case-Based Reasoning System for Functional Test Script Generation with Large Language Models
by: Guo, Siyuan, et al.
Published: (2025)

SIMCOPILOT: Evaluating Large Language Models for Copilot-Style Code Generation
by: Jiang, Mingchao, et al.
Published: (2025)

Uncertainty Awareness of Large Language Models Under Code Distribution Shifts: A Benchmark Study
by: Li, Yufei, et al.
Published: (2024)

Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation
by: Ruiz, Fernando Vallecillos, et al.
Published: (2024)

ReflexiCoder: Teaching Large Language Models to Self-Reflect on Generated Code and Self-Correct It via Reinforcement Learning
by: Jiang, Juyong, et al.
Published: (2026)

Can OpenSource beat ChatGPT? -- A Comparative Study of Large Language Models for Text-to-Code Generation
by: Mayer, Luis, et al.
Published: (2024)

DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
by: Guo, Daya, et al.
Published: (2024)

Evaluation and Improvement of Fault Detection for Large Language Models
by: Hu, Qiang, et al.
Published: (2024)

CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation
by: Peng, Jinjun, et al.
Published: (2025)

Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs
by: Yang, Dayu, et al.
Published: (2025)

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models
by: Jin, Bihui, et al.
Published: (2025)

Evaluating the Process Modeling Abilities of Large Language Models -- Preliminary Foundations and Results
by: Fettke, Peter, et al.
Published: (2025)

CODEMENV: Benchmarking Large Language Models on Code Migration
by: Cheng, Keyuan, et al.
Published: (2025)

Neuron Patching: Semantic-based Neuron-level Language Model Repair for Code Generation
by: Gu, Jian, et al.
Published: (2023)

PurpCode: Reasoning for Safer Code Generation
by: Liu, Jiawei, et al.
Published: (2025)

DDPT: Diffusion-Driven Prompt Tuning for Large Language Model Code Generation
by: Li, Jinyang, et al.
Published: (2025)

Towards Understanding What Code Language Models Learned
by: Ahmed, Toufique, et al.
Published: (2023)

InfiBench: Evaluating the Question-Answering Capabilities of Code Large Language Models
by: Li, Linyi, et al.
Published: (2024)

CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code Generation
by: Yan, Kaiwen, et al.
Published: (2025)

CONCUR: Benchmarking LLMs for Concurrent Code Generation
by: Huang, Jue, et al.
Published: (2026)

RepoQA: Evaluating Long Context Code Understanding
by: Liu, Jiawei, et al.
Published: (2024)

The Impact of Hyperparameters on Large Language Model Inference Performance: An Evaluation of vLLM and HuggingFace Pipelines
by: Martinez, Matias
Published: (2024)

code_transformed: The Influence of Large Language Models on Code
by: Xu, Yuliang, et al.
Published: (2025)

ReCode: Reinforcing Code Generation with Reasoning-Process Rewards
by: Fan, Lishui, et al.
Published: (2025)

Lita: Light Agent Uncovers the Agentic Coding Capabilities of LLMs
by: Dai, Hankun, et al.
Published: (2025)

IntentCoding: Amplifying User Intent in Code Generation
by: Fang, Zheng, et al.
Published: (2026)

SelfCodeAlign: Self-Alignment for Code Generation
by: Wei, Yuxiang, et al.
Published: (2024)