Large Language Models for Code Summarization
Fuente:
arXiv
Saved in:
| Main Authors: | Szalontai, Balázs, Szalay, Gergő, Márton, Tamás, Sike, Anna, Pintér, Balázs, Gregorics, Tibor |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks
by: Kadosh, Tal, et al.
Published: (2023)
by: Kadosh, Tal, et al.
Published: (2023)
A Multi-Expert Large Language Model Architecture for Verilog Code Generation
by: Nadimi, Bardia, et al.
Published: (2024)
by: Nadimi, Bardia, et al.
Published: (2024)
Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
by: Cassano, Federico, et al.
Published: (2023)
by: Cassano, Federico, et al.
Published: (2023)
JavaBench: A Benchmark of Object-Oriented Code Generation for Evaluating Large Language Models
by: Cao, Jialun, et al.
Published: (2024)
by: Cao, Jialun, et al.
Published: (2024)
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates
by: Hooda, Ashish, et al.
Published: (2024)
by: Hooda, Ashish, et al.
Published: (2024)
PerfRL: A Small Language Model Framework for Efficient Code Optimization
by: Duan, Shukai, et al.
Published: (2023)
by: Duan, Shukai, et al.
Published: (2023)
ChatDBG: Augmenting Debugging with Large Language Models
by: Levin, Kyla H., et al.
Published: (2024)
by: Levin, Kyla H., et al.
Published: (2024)
Large Language Models Synergize with Automated Machine Learning
by: Xu, Jinglue, et al.
Published: (2024)
by: Xu, Jinglue, et al.
Published: (2024)
Evaluating Quantized Large Language Models for Code Generation on Low-Resource Language Benchmarks
by: Nyamsuren, Enkhbold
Published: (2024)
by: Nyamsuren, Enkhbold
Published: (2024)
HGAdapter: Hypergraph-based Adapters in Language Models for Code Summarization and Clone Detection
by: Yang, Guang, et al.
Published: (2025)
by: Yang, Guang, et al.
Published: (2025)
Zero-Shot RTL Code Generation with Attention Sink Augmented Large Language Models
by: Sandal, Selim, et al.
Published: (2024)
by: Sandal, Selim, et al.
Published: (2024)
Neural architectures for resolving references in program code
by: Szalay, Gergő, et al.
Published: (2026)
by: Szalay, Gergő, et al.
Published: (2026)
REFLEX: Reference-Free Evaluation of Log Summarization via Large Language Model Judgment
by: Mudgal, Priyanka
Published: (2025)
by: Mudgal, Priyanka
Published: (2025)
EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking
by: Wei, Anjiang, et al.
Published: (2025)
by: Wei, Anjiang, et al.
Published: (2025)
Incoherence as Oracle-less Measure of Error in LLM-Based Code Generation
by: Valentin, Thomas, et al.
Published: (2025)
by: Valentin, Thomas, et al.
Published: (2025)
Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3
by: Sadik, Ahmed R., et al.
Published: (2025)
by: Sadik, Ahmed R., et al.
Published: (2025)
CodeEditorBench: Evaluating Code Editing Capability of Large Language Models
by: Guo, Jiawei, et al.
Published: (2024)
by: Guo, Jiawei, et al.
Published: (2024)
code_transformed: The Influence of Large Language Models on Code
by: Xu, Yuliang, et al.
Published: (2025)
by: Xu, Yuliang, et al.
Published: (2025)
CODEMENV: Benchmarking Large Language Models on Code Migration
by: Cheng, Keyuan, et al.
Published: (2025)
by: Cheng, Keyuan, et al.
Published: (2025)
CodeVisionary: An Agent-based Framework for Evaluating Large Language Models in Code Generation
by: Wang, Xinchen, et al.
Published: (2025)
by: Wang, Xinchen, et al.
Published: (2025)
Investigating the Efficacy of Large Language Models for Code Clone Detection
by: Khajezade, Mohamad, et al.
Published: (2024)
by: Khajezade, Mohamad, et al.
Published: (2024)
CodeIF-Bench: Evaluating Instruction-Following Capabilities of Large Language Models in Interactive Code Generation
by: Wang, Peiding, et al.
Published: (2025)
by: Wang, Peiding, et al.
Published: (2025)
ScenicNL: Generating Probabilistic Scenario Programs from Natural Language
by: Elmaaroufi, Karim, et al.
Published: (2024)
by: Elmaaroufi, Karim, et al.
Published: (2024)
CodeMind: Evaluating Large Language Models for Code Reasoning
by: Liu, Changshu, et al.
Published: (2024)
by: Liu, Changshu, et al.
Published: (2024)
Lita: Light Agent Uncovers the Agentic Coding Capabilities of LLMs
by: Dai, Hankun, et al.
Published: (2025)
by: Dai, Hankun, et al.
Published: (2025)
TokDrift: When LLM Speaks in Subwords but Code Speaks in Grammar
by: Li, Yinxi, et al.
Published: (2025)
by: Li, Yinxi, et al.
Published: (2025)
Linguacodus: A Synergistic Framework for Transformative Code Generation in Machine Learning Pipelines
by: Trofimova, Ekaterina, et al.
Published: (2024)
by: Trofimova, Ekaterina, et al.
Published: (2024)
EffiPair: Improving the Efficiency of LLM-generated Code with Relative Contrastive Feedback
by: Hajizadeh, Samira, et al.
Published: (2026)
by: Hajizadeh, Samira, et al.
Published: (2026)
What can Large Language Models Capture about Code Functional Equivalence?
by: Maveli, Nickil, et al.
Published: (2024)
by: Maveli, Nickil, et al.
Published: (2024)
DDPT: Diffusion-Driven Prompt Tuning for Large Language Model Code Generation
by: Li, Jinyang, et al.
Published: (2025)
by: Li, Jinyang, et al.
Published: (2025)
Analyzing the Performance of Large Language Models on Code Summarization
by: Haldar, Rajarshi, et al.
Published: (2024)
by: Haldar, Rajarshi, et al.
Published: (2024)
Verify Before You Fix: Agentic Execution Grounding for Trustworthy Cross-Language Code Analysis
by: Gajjar, Jugal
Published: (2026)
by: Gajjar, Jugal
Published: (2026)
A Joint Learning Model with Variational Interaction for Multilingual Program Translation
by: Du, Yali, et al.
Published: (2024)
by: Du, Yali, et al.
Published: (2024)
Large Language Models for Multilingual Code Intelligence: A Survey
by: Jiang, Chao, et al.
Published: (2026)
by: Jiang, Chao, et al.
Published: (2026)
$\textbf{PLUM}$: Improving Code LMs with Execution-Guided On-Policy Preference Learning Driven By Synthetic Test Cases
by: Zhang, Dylan, et al.
Published: (2024)
by: Zhang, Dylan, et al.
Published: (2024)
Analysis of AdvFusion: Adapter-based Multilingual Learning for Code Large Language Models
by: Esmaeili, Amirreza, et al.
Published: (2025)
by: Esmaeili, Amirreza, et al.
Published: (2025)
SIMCOPILOT: Evaluating Large Language Models for Copilot-Style Code Generation
by: Jiang, Mingchao, et al.
Published: (2025)
by: Jiang, Mingchao, et al.
Published: (2025)
Perish or Flourish? A Holistic Evaluation of Large Language Models for Code Generation in Functional Programming
by: Lang, Nguyet-Anh H., et al.
Published: (2026)
by: Lang, Nguyet-Anh H., et al.
Published: (2026)
Benchmarking Large Language Models for ABAP Code Generation: An Empirical Study on Iterative Improvement by Compiler Feedback
by: Wallraven, Stephan, et al.
Published: (2026)
by: Wallraven, Stephan, et al.
Published: (2026)
Is Functional Correctness Enough to Evaluate Code Language Models? Exploring Diversity of Generated Codes
by: Chon, Heejae, et al.
Published: (2024)
by: Chon, Heejae, et al.
Published: (2024)
Similar Items
-
MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks
by: Kadosh, Tal, et al.
Published: (2023) -
A Multi-Expert Large Language Model Architecture for Verilog Code Generation
by: Nadimi, Bardia, et al.
Published: (2024) -
Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
by: Cassano, Federico, et al.
Published: (2023) -
JavaBench: A Benchmark of Object-Oriented Code Generation for Evaluating Large Language Models
by: Cao, Jialun, et al.
Published: (2024) -
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates
by: Hooda, Ashish, et al.
Published: (2024)