3 papers
cs.CL2026
EvoFlint: An Evolutionary Atlas of Multi-Turn LLM Vulnerabilities
Feitong Qiao, Liren Peng, Shiming Ren +7
Frontier language models that refuse harmful single-turn prompts often comply when the same intent is reached gradually over many turns, making multi-turn attacks one of the least…
cs.CR2024
Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection
Ira Ceka, Feitong Qiao, Anik Dey +3
Despite their remarkable success, large language models (LLMs) have shown limited ability on safety-critical code tasks such as vulnerability detection. Typically, static analysis…
cs.SE2024
Combining LLM Code Generation with Formal Specifications and Reactive Program Synthesis
William Murphy, Nikolaus Holzer, Feitong Qiao +4
In the past few years, Large Language Models (LLMs) have exploded in usefulness and popularity for code generation tasks. However, LLMs still struggle with accuracy and are unsuita…