4 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.SE2026
SpecCloak: Probing Harmful Code Generation through Engineering Specifications
Wenbin Chen, Jiexin Wang, Guanting Wu +2
The code generation capabilities of large language models (LLMs) can equally be misused to implement harmful functionality, underscoring the need to understand their safety behavio…
cs.AI2026
Strat-Reasoner: Reinforcing Strategic Reasoning of LLMs in Multi-Agent Games
Yidong He, Yutao Lai, Pengxu Yang +4
While Large Language Models (LLMs) excel in certain reasoning tasks, they struggle in multi-agent games where the final outcome depends on the joint strategies of all agents. In mu…
cs.SE2024★ 4 cited
Toward Secure Code Generation: Bridging Correctness and Security via Task-Adaptive Vulnerability Modeling and Execution-Based Benchmarking
Jiexin Wang, Xitong Luo, Liuwen Cao +9
Large language models (LLMs) are increasingly used for program synthesis, yet they often generate code that is functionally plausible but insecure. Progress in secure code generati…