On-the-Fly Input Adaptation for Reliable Code Intelligence
Fuente:
arXiv
Saved in:
| Main Authors: | Rathnasuriya, Ravishka, Yang, Wei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Framework for On the Fly Input Refinement for Deep Learning Models
by: Rathnasuriya, Ravishka
Published: (2025)
by: Rathnasuriya, Ravishka
Published: (2025)
When to Answer and When to Defer: A Decision Framework for Reliable Code Predictions
by: Rathnasuriya, Ravishka, et al.
Published: (2026)
by: Rathnasuriya, Ravishka, et al.
Published: (2026)
CodeImprove: Program Adaptation for Deep Code Models
by: Rathnasuriya, Ravishka, et al.
Published: (2025)
by: Rathnasuriya, Ravishka, et al.
Published: (2025)
Characterizing Real-World Bugs in Tile Programs for Automated Bug Detection
by: Rathnasuriya, Ravishka, et al.
Published: (2026)
by: Rathnasuriya, Ravishka, et al.
Published: (2026)
Can You Mimic Me? Exploring the Use of Android Record & Replay Tools in Debugging
by: Song, Zihe, et al.
Published: (2025)
by: Song, Zihe, et al.
Published: (2025)
HateModerate: Testing Hate Speech Detectors against Content Moderation Policies
by: Zheng, Jiangrui, et al.
Published: (2023)
by: Zheng, Jiangrui, et al.
Published: (2023)
On the Reliability of Code Comprehension Proxies
by: Arvan, Erfan, et al.
Published: (2026)
by: Arvan, Erfan, et al.
Published: (2026)
Enhancing and Reporting Robustness Boundary of Neural Code Models for Intelligent Code Understanding
by: Han, Tingxu, et al.
Published: (2026)
by: Han, Tingxu, et al.
Published: (2026)
Multi-Agent Code-Orchestrated Generation for Reliable Infrastructure-as-Code
by: Khan, Rana Nameer Hussain, et al.
Published: (2025)
by: Khan, Rana Nameer Hussain, et al.
Published: (2025)
Code vs Serialized AST Inputs for LLM-Based Code Summarization: An Empirical Study
by: Dong, Shijia, et al.
Published: (2026)
by: Dong, Shijia, et al.
Published: (2026)
Is LLM-Generated Code More Maintainable \& Reliable than Human-Written Code?
by: Molison, Alfred Santa, et al.
Published: (2025)
by: Molison, Alfred Santa, et al.
Published: (2025)
Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Vision
by: Lu, Xu, et al.
Published: (2025)
by: Lu, Xu, et al.
Published: (2025)
Instructive Code Retriever: Learn from Large Language Model's Feedback for Code Intelligence Tasks
by: Lu, Jiawei, et al.
Published: (2024)
by: Lu, Jiawei, et al.
Published: (2024)
Automatic Generation of Benchmarks and Reliable LLM Judgment for Code Tasks
by: Farchi, Eitan, et al.
Published: (2024)
by: Farchi, Eitan, et al.
Published: (2024)
Coding in a Bubble? Evaluating LLMs in Resolving Context Adaptation Bugs During Code Adaptation
by: Zhang, Tanghaoran, et al.
Published: (2026)
by: Zhang, Tanghaoran, et al.
Published: (2026)
Algorithm-Based Pipeline for Reliable and Intent-Preserving Code Translation with LLMs
by: Dipto, Shahriar Rumi, et al.
Published: (2026)
by: Dipto, Shahriar Rumi, et al.
Published: (2026)
Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems
by: Rathnasuriya, Ravishka, et al.
Published: (2025)
by: Rathnasuriya, Ravishka, et al.
Published: (2025)
Automated Prompt Generation for Code Intelligence: An Empirical study and Experience in WeChat
by: Ji, Kexing, et al.
Published: (2025)
by: Ji, Kexing, et al.
Published: (2025)
On-the-Fly Syntax Highlighting: Generalisation and Speed-ups
by: Palma, Marco Edoardo, et al.
Published: (2024)
by: Palma, Marco Edoardo, et al.
Published: (2024)
PenForge: On-the-Fly Expert Agent Construction for Automated Penetration Testing
by: Huang, Huihui, et al.
Published: (2026)
by: Huang, Huihui, et al.
Published: (2026)
A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities
by: Li, Yaoxian, et al.
Published: (2022)
by: Li, Yaoxian, et al.
Published: (2022)
Enhancing Code Annotation Reliability: Generative AI's Role in Comment Quality Assessment Models
by: Killivalavan, Seetharam, et al.
Published: (2024)
by: Killivalavan, Seetharam, et al.
Published: (2024)
ConAIR:Consistency-Augmented Iterative Interaction Framework to Enhance the Reliability of Code Generation
by: Dong, Jinhao, et al.
Published: (2024)
by: Dong, Jinhao, et al.
Published: (2024)
FlyCatcher: Neural Inference of Runtime Checkers from Tests
by: Souza, Beatriz, et al.
Published: (2026)
by: Souza, Beatriz, et al.
Published: (2026)
Tokalator: A Context Engineering Toolkit for Artificial Intelligence Coding Assistants
by: Farajijobehdar, Vahid, et al.
Published: (2026)
by: Farajijobehdar, Vahid, et al.
Published: (2026)
From Mirage to Grounding: Towards Reliable Multimodal Circuit-to-Verilog Code Generation
by: Yang, Guang, et al.
Published: (2026)
by: Yang, Guang, et al.
Published: (2026)
LLM-based Multi-Agent System for Intelligent Refactoring of Haskell Code
by: Siddeeq, Shahbaz, et al.
Published: (2025)
by: Siddeeq, Shahbaz, et al.
Published: (2025)
What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?
by: Gao, Shuzheng, et al.
Published: (2023)
by: Gao, Shuzheng, et al.
Published: (2023)
Sentiment Analysis of ML Projects: Bridging Emotional Intelligence and Code Quality
by: Ahmed, Md Shoaib, et al.
Published: (2024)
by: Ahmed, Md Shoaib, et al.
Published: (2024)
Input Reduction Enhanced LLM-based Program Repair
by: Yang, Boyang, et al.
Published: (2025)
by: Yang, Boyang, et al.
Published: (2025)
LLM-as-a-Judge for Human-AI Co-Creation: A Reliability-Aware Evaluation Framework for Coding
by: Amin, Md Faizul Ibne, et al.
Published: (2026)
by: Amin, Md Faizul Ibne, et al.
Published: (2026)
Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators
by: Zhang, Kunpeng, et al.
Published: (2025)
by: Zhang, Kunpeng, et al.
Published: (2025)
Wired for Reuse: Automating Context-Aware Code Adaptation in IDEs via LLM-Based Agent
by: Wang, Taiming, et al.
Published: (2025)
by: Wang, Taiming, et al.
Published: (2025)
On the Road to Personalized Code Intelligence: Portraiting and Assisting Developers Based on Their In-IDE Behaviors
by: Liu, Yuhong, et al.
Published: (2026)
by: Liu, Yuhong, et al.
Published: (2026)
Rethinking the effects of data contamination in Code Intelligence
by: Yang, Zhen, et al.
Published: (2025)
by: Yang, Zhen, et al.
Published: (2025)
EfficientUICoder: Efficient MLLM-based UI Code Generation via Input and Output Token Compression
by: Xiao, Jingyu, et al.
Published: (2025)
by: Xiao, Jingyu, et al.
Published: (2025)
A Systematic Literature Review of Code Hallucinations in LLMs: Characterization, Mitigation Methods, Challenges, and Future Directions for Reliable AI
by: Gao, Cuiyun, et al.
Published: (2025)
by: Gao, Cuiyun, et al.
Published: (2025)
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit
by: Wan, Yao, et al.
Published: (2023)
by: Wan, Yao, et al.
Published: (2023)
Demonstration Attack against In-Context Learning for Code Intelligence
by: Ge, Yifei, et al.
Published: (2024)
by: Ge, Yifei, et al.
Published: (2024)
Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency
by: Ashrafi, Nazmus, et al.
Published: (2025)
by: Ashrafi, Nazmus, et al.
Published: (2025)
Similar Items
-
Framework for On the Fly Input Refinement for Deep Learning Models
by: Rathnasuriya, Ravishka
Published: (2025) -
When to Answer and When to Defer: A Decision Framework for Reliable Code Predictions
by: Rathnasuriya, Ravishka, et al.
Published: (2026) -
CodeImprove: Program Adaptation for Deep Code Models
by: Rathnasuriya, Ravishka, et al.
Published: (2025) -
Characterizing Real-World Bugs in Tile Programs for Automated Bug Detection
by: Rathnasuriya, Ravishka, et al.
Published: (2026) -
Can You Mimic Me? Exploring the Use of Android Record & Replay Tools in Debugging
by: Song, Zihe, et al.
Published: (2025)