Saved in:
| Main Author: | Trans, Pseudo |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2026
|
| Online Access: | https://doi.org/10.5281/zenodo.18793262 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
Unraveling the Potential of Large Language Models in Code Translation: How Far Are We?
by: Tao, Qingxiao, et al.
Published: (2024)
by: Tao, Qingxiao, et al.
Published: (2024)
Vulnerability Detection with Code Language Models: How Far Are We?
by: Ding, Yangruibo, et al.
Published: (2024)
by: Ding, Yangruibo, et al.
Published: (2024)
How Far Have We Gone in Binary Code Understanding Using Large Language Models
by: Shang, Xiuwei, et al.
Published: (2024)
by: Shang, Xiuwei, et al.
Published: (2024)
Large Language Models for Equivalent Mutant Detection: How Far Are We?
by: Tian, Zhao, et al.
Published: (2024)
by: Tian, Zhao, et al.
Published: (2024)
Mexican Hometown Associations in the U.S.: Motives for Transnational Engagement
by: Lars Ove Trans
Published: (2009)
by: Lars Ove Trans
Published: (2009)
Model Editing for LLMs4Code: How Far are We?
by: Li, Xiaopeng, et al.
Published: (2024)
by: Li, Xiaopeng, et al.
Published: (2024)
How Far Can We Extract Diverse Perspectives from Large Language Models?
by: Hayati, Shirley Anugrah, et al.
Published: (2023)
by: Hayati, Shirley Anugrah, et al.
Published: (2023)
PrepBench: How Far Are We from Natural-Language-Driven Data Preparation?
by: Xu, Jingzhe, et al.
Published: (2026)
by: Xu, Jingzhe, et al.
Published: (2026)
MotiveBench: How Far Are We From Human-Like Motivational Reasoning in Large Language Models?
by: Yong, Xixian, et al.
Published: (2025)
by: Yong, Xixian, et al.
Published: (2025)
An Empirical Study on Automatically Detecting AI-Generated Source Code: How Far Are We?
by: Suh, Hyunjae, et al.
Published: (2024)
by: Suh, Hyunjae, et al.
Published: (2024)
Leveraging Language Models for Log Statement Generation in Multilingual Scenarios: How Far Are We?
by: Kusama, Kazuki, et al.
Published: (2026)
by: Kusama, Kazuki, et al.
Published: (2026)
How Far Are We from True Unlearnability?
by: Ye, Kai, et al.
Published: (2025)
by: Ye, Kai, et al.
Published: (2025)
LLMs for Relational Reasoning: How Far are We?
by: Li, Zhiming, et al.
Published: (2024)
by: Li, Zhiming, et al.
Published: (2024)
Large Language Models for Predictive Analysis: How Far Are They?
by: Chen, Qin, et al.
Published: (2025)
by: Chen, Qin, et al.
Published: (2025)
How Far Are We From AGI: Are LLMs All We Need?
by: Feng, Tao, et al.
Published: (2024)
by: Feng, Tao, et al.
Published: (2024)
A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?
by: Jiang, Zhihan, et al.
Published: (2023)
by: Jiang, Zhihan, et al.
Published: (2023)
Position Restructuring at Peking University Library.
by: Gao, Zhuo-Xian, et al.
Published: (2001)
by: Gao, Zhuo-Xian, et al.
Published: (2001)
How Far Are We from Generating Missing Modalities with Foundation Models?
by: Ke, Guanzhou, et al.
Published: (2025)
by: Ke, Guanzhou, et al.
Published: (2025)
How Far Are We From True Auto-Research?
by: Zhang, Zhengxin, et al.
Published: (2026)
by: Zhang, Zhengxin, et al.
Published: (2026)
How Far Are We from Optimal Reasoning Efficiency?
by: Gao, Jiaxuan, et al.
Published: (2025)
by: Gao, Jiaxuan, et al.
Published: (2025)
Duplicate Bug Report Detection: How Far Are We?
by: Zhang, Ting, et al.
Published: (2022)
by: Zhang, Ting, et al.
Published: (2022)
Vulnerability-Affected Versions Identification: How Far Are We?
by: Chen, Xingchu, et al.
Published: (2025)
by: Chen, Xingchu, et al.
Published: (2025)
Retrieval-Augmented Test Generation: How Far Are We?
by: Shin, Jiho, et al.
Published: (2024)
by: Shin, Jiho, et al.
Published: (2024)
Portfolio Assessment: How Far Have We Come?
by: Brown, Carol A.
Published: (2002)
by: Brown, Carol A.
Published: (2002)
Residual Risk Analysis in Benign Code: How Far Are We? A Multi-Model Semantic and Structural Similarity Approach
by: Farhad, Mohammad, et al.
Published: (2026)
by: Farhad, Mohammad, et al.
Published: (2026)
Automated Code-centric Software Vulnerability Assessment: How Far Are We? An Empirical Study in C/C++
by: Nguyen, Anh The, et al.
Published: (2024)
by: Nguyen, Anh The, et al.
Published: (2024)
Automatic Data Labeling for Software Vulnerability Prediction Models: How Far Are We?
by: Le, Triet H. M., et al.
Published: (2024)
by: Le, Triet H. M., et al.
Published: (2024)
Deep Learning Framework Testing via Model Mutation: How Far Are We?
by: Mu, Yanzhou, et al.
Published: (2025)
by: Mu, Yanzhou, et al.
Published: (2025)
Can AI Agents Generate Microservices? How Far are We?
by: Adnan, Bassam, et al.
Published: (2026)
by: Adnan, Bassam, et al.
Published: (2026)
Automated Testing of Task-based Chatbots: How Far Are We?
by: Clerissi, Diego, et al.
Published: (2026)
by: Clerissi, Diego, et al.
Published: (2026)
The AI Hippocampus: How Far are We From Human Memory?
by: Jia, Zixia, et al.
Published: (2026)
by: Jia, Zixia, et al.
Published: (2026)
Representation Learning for Stack Overflow Posts: How Far are We?
by: He, Junda, et al.
Published: (2023)
by: He, Junda, et al.
Published: (2023)
The Digital Cybersecurity Expert: How Far Have We Come?
by: Wang, Dawei, et al.
Published: (2025)
by: Wang, Dawei, et al.
Published: (2025)
How Far Are We from Intelligent Visual Deductive Reasoning?
by: Zhang, Yizhe, et al.
Published: (2024)
by: Zhang, Yizhe, et al.
Published: (2024)
Using LLMs for Security Advisory Investigations: How Far Are We?
by: Abdullah, Bayu Fedra, et al.
Published: (2025)
by: Abdullah, Bayu Fedra, et al.
Published: (2025)
LLM For Loop Invariant Generation and Fixing: How Far Are We?
by: Akhond, Mostafijur Rahman, et al.
Published: (2025)
by: Akhond, Mostafijur Rahman, et al.
Published: (2025)
Fairness Improvement with Multiple Protected Attributes: How Far Are We?
by: Chen, Zhenpeng, et al.
Published: (2023)
by: Chen, Zhenpeng, et al.
Published: (2023)
Deep Learning-Based Out-of-distribution Source Code Data Identification: How Far Have We Gone?
by: Nguyen, Van, et al.
Published: (2024)
by: Nguyen, Van, et al.
Published: (2024)
ImageAttributionBench: How Far Are We from Generalizable Attribution?
by: Mou, Tingshu, et al.
Published: (2026)
by: Mou, Tingshu, et al.
Published: (2026)
Similar Items
-
Specification-Driven Code Translation Powered by Large Language Models: How Far Are We?
by: Saha, Soumit Kanti, et al.
Published: (2024) -
Unraveling the Potential of Large Language Models in Code Translation: How Far Are We?
by: Tao, Qingxiao, et al.
Published: (2024) -
Vulnerability Detection with Code Language Models: How Far Are We?
by: Ding, Yangruibo, et al.
Published: (2024) -
How Far Have We Gone in Binary Code Understanding Using Large Language Models
by: Shang, Xiuwei, et al.
Published: (2024) -
Large Language Models for Equivalent Mutant Detection: How Far Are We?
by: Tian, Zhao, et al.
Published: (2024)