From the 1 of 18 linked papers with an AI index.
2 citations · 2 across the 9 of their papers we have counts for
18 papers
AgentExecutor: Partial Code Execution via Agentic Context Generation
Junkai Chen, Chengran Yang, Xing Hu +3
Executing code snippets is essential for dynamic program analysis, but it remains challenging to execute an arbitrary code snippet due to issues like missing context and incomplete…
Exploring and Bridging Knowledge Holes in Unlearned Multimodal Large Language Models
Junxiang You, Junkai Chen, Yuhao He +3
Machine unlearning offers a promising approach to remove unsafe content from Multimodal Large Language Models (MLLMs), yet ensuring the precision of unlearning remains a persistent…
Toward Fine-Grained Forgetting:Attribute Unlearning for Multimodal Large Language Models
Junkai Lin, Junkai Chen, Siqi Hou +5
Multimodal large language models (MLLMs) exhibit strong vision--language capabilities but may also memorize and disclose sensitive information. Machine unlearning seeks to remove d…
SWE-NFI: Studying and Benchmarking Coding Agents for Non-Functional Improvements
Pengyu Xue, He Yang Yuan, Xin Wang +6
The paper introduces SWE-NFI, a benchmark that assesses how coding agents can make non-functional, behavior-preserving improvements to Python code, using real pull‑request tasks an…
EPIC: Abstraction and Polymorphism of In-Network Collectives on Ethernet
Yitao Yuan, Jianglong Nie, Tianyu Bai +28
In-Network Collective (INC) acceleration holds immense potential for optimizing AI training and inference; however, its cross-layer nature has historically hindered investment and…
SecureVibeBench: Benchmarking Secure Vibe Coding of AI Agents via Reconstructing Vulnerability-Introducing Scenarios
Junkai Chen, Huihui Huang, Yunbo Lyu +10
Large language model-powered code agents are rapidly transforming software engineering, yet the security risks of their generated code have become a critical concern. Existing benc…