From the 1 of 8 linked papers with an AI index.
8 papers
MultiFixer: A Coordinator-Proposer Based Multi-Agent Framework For Fixing Multi-Hunk Bugs
Haichuan Hu, Chunrong Fang, Ye Shang +5
The paper introduces MultiFixer, a multi-agent framework that uses a Coordinator‑Proposer architecture to coordinate large language model generated patches for fixing bugs that spa…
Rise From The Ashes: LLM-based Static Analysis for Deep Learning Framework Bugs
Shaoyu Yang, Haifeng Lin, Chunrong Fang +6
Deep learning (DL) frameworks are critical AI infrastructures that often hide bugs with serious security implications. While dynamic approaches such as fuzzing are effective in unc…
EvoRepair: Enhancing Vulnerability Repair Agents Through Experience-Based Self-Evolution
Haichuan Hu, Guoqing Xie, Quanjun Zhang +5
Large Language Models (LLMs) have shown promise for automated vulnerability repair (AVR), but they still face several limitations, including the lack of intra-vulnerability experie…
SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction
Jiawei He, Mengyu Shi, Jiawei Liu +6
Joint Entity and Relation Extraction (JERE) is highly sensitive to training data quality, making data augmentation a natural way to improve generalization. However, existing augmen…
SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks?
Hwiwon Lee, Jiawei Liu, Dongjun Kim +4
Finding a real vulnerability in complicated systems is a challenging, long-horizon task that demands reasoning across an entire codebase to produce a working proof-of-concept (PoC)…
ATTest: Agent-Driven Tensor Testing for Deep Learning Library Modules
Zhengyu Zhan, Ye Shang, Jiawei Liu +3
The unit testing of Deep Learning (DL) libraries is challenging due to complex numerical semantics and implicit tensor constraints. Traditional Search-Based Software Testing (SBST)…