RITFIS: Robust input testing framework for LLMs-based intelligent software
Fuente:
arXiv
Saved in:
| Main Authors: | Xiao, Mingxuan, Xiao, Yan, Dong, Hai, Ji, Shunhui, Zhang, Pengcheng |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BASFuzz: Towards Robustness Evaluation of LLM-based NLP Software via Automated Fuzz Testing
by: Xiao, Mingxuan, et al.
Published: (2025)
by: Xiao, Mingxuan, et al.
Published: (2025)
ABFS: Natural Robustness Testing for LLM-based NLP Software
by: Xiao, Mingxuan, et al.
Published: (2025)
by: Xiao, Mingxuan, et al.
Published: (2025)
Assessing the Robustness of LLM-based NLP Software via Automated Testing
by: Xiao, Mingxuan, et al.
Published: (2024)
by: Xiao, Mingxuan, et al.
Published: (2024)
HGA: Heuristic Black‐Box Test Case Generation for NLP Intelligent Software
by: Mingxuan Xiao, et al.
Published: (2026)
by: Mingxuan Xiao, et al.
Published: (2026)
NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations
by: Chen, Junkai, et al.
Published: (2024)
by: Chen, Junkai, et al.
Published: (2024)
CodeHalu: Investigating Code Hallucinations in LLMs via Execution-based Verification
by: Tian, Yuchen, et al.
Published: (2024)
by: Tian, Yuchen, et al.
Published: (2024)
AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions
by: Wang, Zihan, et al.
Published: (2025)
by: Wang, Zihan, et al.
Published: (2025)
Benchmarking LLMs for Unit Test Generation from Real-World Functions
by: Huang, Dong, et al.
Published: (2025)
by: Huang, Dong, et al.
Published: (2025)
CodeSpecBench: Benchmarking LLMs for Executable Behavioral Specification Generation
by: Chen, Zaoyu, et al.
Published: (2026)
by: Chen, Zaoyu, et al.
Published: (2026)
Model Editing for LLMs4Code: How Far are We?
by: Li, Xiaopeng, et al.
Published: (2024)
by: Li, Xiaopeng, et al.
Published: (2024)
Unlocking a New Rust Programming Experience: Fast and Slow Thinking with LLMs to Conquer Undefined Behaviors
by: Jiang, Renshuang, et al.
Published: (2025)
by: Jiang, Renshuang, et al.
Published: (2025)
SGDL: Smart contract vulnerability generation via deep learning
by: Hanting Chu, et al.
Published: (2024)
by: Hanting Chu, et al.
Published: (2024)
Multi-Programming Language Sandbox for LLMs
by: Dou, Shihan, et al.
Published: (2024)
by: Dou, Shihan, et al.
Published: (2024)
Octopus: On-device language model for function calling of software APIs
by: Chen, Wei, et al.
Published: (2024)
by: Chen, Wei, et al.
Published: (2024)
HumanEval Pro and MBPP Pro: Evaluating Large Language Models on Self-invoking Code Generation
by: Yu, Zhaojian, et al.
Published: (2024)
by: Yu, Zhaojian, et al.
Published: (2024)
Humanity's Last Code Exam: Can Advanced LLMs Conquer Human's Hardest Code Competition?
by: Li, Xiangyang, et al.
Published: (2025)
by: Li, Xiangyang, et al.
Published: (2025)
IABC‐TCG: Improved artificial bee colony algorithm‐based test case generation for smart contracts
by: Shunhui Ji, et al.
Published: (2024)
by: Shunhui Ji, et al.
Published: (2024)
Risk-based test framework for LLM features in regulated software
by: Zhou, Zhiyin
Published: (2026)
by: Zhou, Zhiyin
Published: (2026)
LogLM: From Task-based to Instruction-based Automated Log Analysis
by: Liu, Yilun, et al.
Published: (2024)
by: Liu, Yilun, et al.
Published: (2024)
LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs
by: Xia, Yunhui, et al.
Published: (2025)
by: Xia, Yunhui, et al.
Published: (2025)
Is Your Benchmark (Still) Useful? Dynamic Benchmarking for Code Language Models
by: Guan, Batu, et al.
Published: (2025)
by: Guan, Batu, et al.
Published: (2025)
Leveraging LLMs for Grammar Adaptation: A Study on Metamodel-Grammar Co-Evolution
by: Zhang, Weixing, et al.
Published: (2026)
by: Zhang, Weixing, et al.
Published: (2026)
StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback
by: Dou, Shihan, et al.
Published: (2024)
by: Dou, Shihan, et al.
Published: (2024)
DiffuTester: Accelerating Unit Test Generation for Diffusion LLMs via Mining Structural Pattern
by: Yang, Lekang, et al.
Published: (2025)
by: Yang, Lekang, et al.
Published: (2025)
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
by: Wang, Junqiao, et al.
Published: (2024)
by: Wang, Junqiao, et al.
Published: (2024)
Solver-Independent Automated Problem Formulation via LLMs for High-Cost Simulation-Driven Design
by: Li, Yuchen, et al.
Published: (2025)
by: Li, Yuchen, et al.
Published: (2025)
Evaluation of Code LLMs on Geospatial Code Generation
by: Gramacki, Piotr, et al.
Published: (2024)
by: Gramacki, Piotr, et al.
Published: (2024)
LLMs in Mobile Apps: Practices, Challenges, and Opportunities
by: Hau, Kimberly, et al.
Published: (2025)
by: Hau, Kimberly, et al.
Published: (2025)
From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future
by: Jin, Haolin, et al.
Published: (2024)
by: Jin, Haolin, et al.
Published: (2024)
MathDuels: Evaluating LLMs as Problem Posers and Solvers
by: Xu, Zhiqiu, et al.
Published: (2026)
by: Xu, Zhiqiu, et al.
Published: (2026)
DependEval: Benchmarking LLMs for Repository Dependency Understanding
by: Du, Junjia, et al.
Published: (2025)
by: Du, Junjia, et al.
Published: (2025)
TestExplora: Benchmarking LLMs for Proactive Bug Discovery via Repository-Level Test Generation
by: Liu, Steven, et al.
Published: (2026)
by: Liu, Steven, et al.
Published: (2026)
How to Select Pre-Trained Code Models for Reuse? A Learning Perspective
by: Bi, Zhangqian, et al.
Published: (2025)
by: Bi, Zhangqian, et al.
Published: (2025)
Showing LLM-Generated Code Selectively Based on Confidence of LLMs
by: Li, Jia, et al.
Published: (2024)
by: Li, Jia, et al.
Published: (2024)
FairCoder: Evaluating Social Bias of LLMs in Code Generation
by: Du, Yongkang, et al.
Published: (2025)
by: Du, Yongkang, et al.
Published: (2025)
Coffee: Boost Your Code LLMs by Fixing Bugs with Feedback
by: Moon, Seungjun, et al.
Published: (2023)
by: Moon, Seungjun, et al.
Published: (2023)
Bias Testing and Mitigation in Black Box LLMs using Metamorphic Relations
by: Salimian, Sina, et al.
Published: (2025)
by: Salimian, Sina, et al.
Published: (2025)
AdaCCD: Adaptive Semantic Contrasts Discovery Based Cross Lingual Adaptation for Code Clone Detection
by: Du, Yangkai, et al.
Published: (2023)
by: Du, Yangkai, et al.
Published: (2023)
A Semantic-based Optimization Approach for Repairing LLMs: Case Study on Code Generation
by: Gu, Jian, et al.
Published: (2025)
by: Gu, Jian, et al.
Published: (2025)
SimCT: A Simple Consistency Test Protocol in LLMs Development Lifecycle
by: Zhao, Fufangchen, et al.
Published: (2024)
by: Zhao, Fufangchen, et al.
Published: (2024)
Similar Items
-
BASFuzz: Towards Robustness Evaluation of LLM-based NLP Software via Automated Fuzz Testing
by: Xiao, Mingxuan, et al.
Published: (2025) -
ABFS: Natural Robustness Testing for LLM-based NLP Software
by: Xiao, Mingxuan, et al.
Published: (2025) -
Assessing the Robustness of LLM-based NLP Software via Automated Testing
by: Xiao, Mingxuan, et al.
Published: (2024) -
HGA: Heuristic Black‐Box Test Case Generation for NLP Intelligent Software
by: Mingxuan Xiao, et al.
Published: (2026) -
NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations
by: Chen, Junkai, et al.
Published: (2024)