SpecTra: Enhancing the Code Translation Ability of Language Models by Generating Multi-Modal Specifications
Fuente:
arXiv
Saved in:
| Main Authors: | Nitin, Vikram, Krishna, Rahul, Ray, Baishakhi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
C2SaferRust: Transforming C Projects into Safer Rust with NeuroSymbolic Techniques
by: Nitin, Vikram, et al.
Published: (2025)
by: Nitin, Vikram, et al.
Published: (2025)
FaultLine: Automated Proof-of-Vulnerability Generation Using LLM Agents
by: Nitin, Vikram, et al.
Published: (2025)
by: Nitin, Vikram, et al.
Published: (2025)
Code Quality Analysis of Translations from C to Rust
by: Tadesse, Biruk, et al.
Published: (2026)
by: Tadesse, Biruk, et al.
Published: (2026)
Yuga: Automatically Detecting Lifetime Annotation Bugs in the Rust Language
by: Nitin, Vikram, et al.
Published: (2023)
by: Nitin, Vikram, et al.
Published: (2023)
LibEvolutionEval: A Benchmark and Study for Version-Specific Code Generation
by: Kuhar, Sachit, et al.
Published: (2024)
by: Kuhar, Sachit, et al.
Published: (2024)
SpecEval: Evaluating Code Comprehension in Large Language Models via Program Specifications
by: Ma, Lezhi, et al.
Published: (2024)
by: Ma, Lezhi, et al.
Published: (2024)
Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data Contamination
by: Chen, Simin, et al.
Published: (2025)
by: Chen, Simin, et al.
Published: (2025)
CodeFort: Robust Training for Code Generation Models
by: Zhang, Yuhao, et al.
Published: (2024)
by: Zhang, Yuhao, et al.
Published: (2024)
CYCLE: Learning to Self-Refine the Code Generation
by: Ding, Yangruibo, et al.
Published: (2024)
by: Ding, Yangruibo, et al.
Published: (2024)
DiffSpec: Differential Testing with LLMs using Natural Language Specifications and Code Artifacts
by: Rao, Nikitha, et al.
Published: (2024)
by: Rao, Nikitha, et al.
Published: (2024)
SpecGen: Automated Generation of Formal Program Specifications via Large Language Models
by: Ma, Lezhi, et al.
Published: (2024)
by: Ma, Lezhi, et al.
Published: (2024)
CodeAssistBench (CAB): Dataset & Benchmarking for Multi-turn Chat-Based Code Assistance
by: Kim, Myeongsoo, et al.
Published: (2025)
by: Kim, Myeongsoo, et al.
Published: (2025)
Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code
by: Pan, Rangeet, et al.
Published: (2023)
by: Pan, Rangeet, et al.
Published: (2023)
CodeSpecBench: Benchmarking LLMs for Executable Behavioral Specification Generation
by: Chen, Zaoyu, et al.
Published: (2026)
by: Chen, Zaoyu, et al.
Published: (2026)
Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
by: Ryan, Gabriel, et al.
Published: (2024)
by: Ryan, Gabriel, et al.
Published: (2024)
Automated Code Editing with Search-Generate-Modify
by: Liu, Changshu, et al.
Published: (2023)
by: Liu, Changshu, et al.
Published: (2023)
Specification-Driven Code Translation Powered by Large Language Models: How Far Are We?
by: Saha, Soumit Kanti, et al.
Published: (2024)
by: Saha, Soumit Kanti, et al.
Published: (2024)
SpecPylot: Python Specification Generation using Large Language Models
by: Ayon, Ragib Shahariar, et al.
Published: (2026)
by: Ayon, Ragib Shahariar, et al.
Published: (2026)
Vulnerability Detection with Code Language Models: How Far Are We?
by: Ding, Yangruibo, et al.
Published: (2024)
by: Ding, Yangruibo, et al.
Published: (2024)
SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning
by: Ding, Yangruibo, et al.
Published: (2024)
by: Ding, Yangruibo, et al.
Published: (2024)
CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation
by: Peng, Jinjun, et al.
Published: (2025)
by: Peng, Jinjun, et al.
Published: (2025)
Enhancing Cross-Language Code Translation via Task-Specific Embedding Alignment in Retrieval-Augmented Generation
by: Bhattarai, Manish, et al.
Published: (2024)
by: Bhattarai, Manish, et al.
Published: (2024)
ScarfBench: A Benchmark for Cross-Framework Application Migration in Enterprise Java
by: Pavuluri, Advait, et al.
Published: (2026)
by: Pavuluri, Advait, et al.
Published: (2026)
Trustworthy AI Software Engineers
by: Aleti, Aldeida, et al.
Published: (2026)
by: Aleti, Aldeida, et al.
Published: (2026)
Red Teaming Program Repair Agents: When Correct Patches can Hide Vulnerabilities
by: Chen, Simin, et al.
Published: (2025)
by: Chen, Simin, et al.
Published: (2025)
AutoSpec: Automated Generation of Neural Network Specifications
by: Jin, Shuowei, et al.
Published: (2024)
by: Jin, Shuowei, et al.
Published: (2024)
On the Effectiveness of Large Language Models in Domain-Specific Code Generation
by: Gu, Xiaodong, et al.
Published: (2023)
by: Gu, Xiaodong, et al.
Published: (2023)
KGym: A Platform and Dataset to Benchmark Large Language Models on Linux Kernel Crash Resolution
by: Mathai, Alex, et al.
Published: (2024)
by: Mathai, Alex, et al.
Published: (2024)
CodeReasoner: Enhancing the Code Reasoning Ability with Reinforcement Learning
by: Tang, Lingxiao, et al.
Published: (2025)
by: Tang, Lingxiao, et al.
Published: (2025)
Fixing Large Language Models' Specification Misunderstanding for Better Code Generation
by: Tian, Zhao, et al.
Published: (2023)
by: Tian, Zhao, et al.
Published: (2023)
REFINE: Enhancing Program Repair Agents through Context-Aware Patch Refinement
by: Pabba, Anvith, et al.
Published: (2025)
by: Pabba, Anvith, et al.
Published: (2025)
Code Reasoning for Software Engineering Tasks: A Survey and A Call to Action
by: Pujar, Saurabh, et al.
Published: (2025)
by: Pujar, Saurabh, et al.
Published: (2025)
CodeSense: a Real-World Benchmark and Dataset for Code Semantic Reasoning
by: Roy, Monoshi Kumar, et al.
Published: (2025)
by: Roy, Monoshi Kumar, et al.
Published: (2025)
Terminus-4B: Can a Smaller Model Replace Frontier LLMs at Agentic Execution Tasks?
by: Garg, Spandan, et al.
Published: (2026)
by: Garg, Spandan, et al.
Published: (2026)
SpecAgent: A Speculative Retrieval and Forecasting Agent for Code Completion
by: Ma, George, et al.
Published: (2025)
by: Ma, George, et al.
Published: (2025)
EditLord: Learning Code Transformation Rules for Code Editing
by: Li, Weichen, et al.
Published: (2025)
by: Li, Weichen, et al.
Published: (2025)
Cross-Task Benchmarking and Evaluation of General-Purpose and Code-Specific Large Language Models
by: Das, Gunjan, et al.
Published: (2025)
by: Das, Gunjan, et al.
Published: (2025)
AutoReSpec: A Framework for Generating Specification using Large Language Models
by: Ayon, Ragib Shahariar, et al.
Published: (2026)
by: Ayon, Ragib Shahariar, et al.
Published: (2026)
Evaluating Code Reasoning Abilities of Large Language Models Under Real-World Settings
by: Liu, Changshu, et al.
Published: (2025)
by: Liu, Changshu, et al.
Published: (2025)
Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation
by: Bhattarai, Manish, et al.
Published: (2024)
by: Bhattarai, Manish, et al.
Published: (2024)
Similar Items
-
C2SaferRust: Transforming C Projects into Safer Rust with NeuroSymbolic Techniques
by: Nitin, Vikram, et al.
Published: (2025) -
FaultLine: Automated Proof-of-Vulnerability Generation Using LLM Agents
by: Nitin, Vikram, et al.
Published: (2025) -
Code Quality Analysis of Translations from C to Rust
by: Tadesse, Biruk, et al.
Published: (2026) -
Yuga: Automatically Detecting Lifetime Annotation Bugs in the Rust Language
by: Nitin, Vikram, et al.
Published: (2023) -
LibEvolutionEval: A Benchmark and Study for Version-Specific Code Generation
by: Kuhar, Sachit, et al.
Published: (2024)