24 citations · 33 across the 11 of their papers we have counts for
11 papers
Parser-Free Querying of Security Logs
Evan Luo, Julien Piet, David Wagner
Security analysts routinely query system logs to detect threats and investigate incidents, but each log source uses its own semi-structured format: logs are cheap to produce, but e…
Trojan Hippo Bench: A Dynamic Benchmark for Persistent Memory Attacks and Defenses in LLM Agents
Debeshee Das, Julien Piet, Darya Kaviani +3
Memory systems enable otherwise stateless LLM agents to persist user information across sessions, but also introduce a new attack surface. The Trojan Hippo attack is a class of per…
Web Agents Should Adopt the Compile-and-Execute Paradigm
Julien Piet, Annabella Chow, Yiwei Hou +5
ReAct has become the default architecture across LLM agents, and many existing web agents follow this paradigm. We argue that it is the wrong default for web agents. Instead, web a…
Semantic-Aware Parsing for Security Logs
Julien Piet, Vivian Fang, Rishi Khare +4
Security logs are foundational to threat detection and post-incident investigation, yet analysts often struggle to fully leverage them due to their heterogeneity and unstructured n…
JailbreaksOverTime: Detecting Jailbreak Attacks Under Distribution Shift
Julien Piet, Xiao Huang, Dennis Jacob +7
Safety and security remain critical concerns in AI deployment. Despite safety training through reinforcement learning with human feedback (RLHF) [ 32], language models remain vulne…
Toxicity Detection for Free
Zhanhao Hu, Julien Piet, Geng Zhao +2
Current LLMs are generally aligned to follow safety requirements and tend to refuse toxic prompts. However, LLMs can fail to refuse toxic prompts or be overcautious and refuse beni…
StruQ: Defending Against Prompt Injection with Structured Queries
Sizhe Chen, Julien Piet, Chawin Sitawarin +1
Recent advances in Large Language Models (LLMs) enable exciting LLM-integrated applications, which perform text-based tasks by utilizing their advanced language understanding capab…
Jatmo: Prompt Injection Defense by Task-Specific Finetuning
Julien Piet, Maha Alrashed, Chawin Sitawarin +5
Large Language Models (LLMs) are attracting significant research attention due to their instruction-following abilities, allowing users and developers to leverage LLMs for a variet…
Mark My Words: Analyzing and Evaluating Language Model Watermarks
Julien Piet, Chawin Sitawarin, Vivian Fang +2
The capabilities of large language models have grown significantly in recent years and so too have concerns about their misuse. It is important to be able to distinguish machine-ge…
Asymmetric Certified Robustness via Feature-Convex Neural Networks
Samuel Pfrommer, Brendon G. Anderson, Julien Piet +1
Recent works have introduced input-convex neural networks (ICNNs) as learning models with advantageous training, inference, and generalization properties linked to their convex str…
Extracting Godl [sic] from the Salt Mines: Ethereum Miners Extracting Value
Julien Piet, Jaiden Fairoze, Nicholas Weaver
Cryptocurrency miners have great latitude in deciding which transactions they accept, including their own, and the order in which they accept them. Ethereum miners in particular us…