3 papers
cs.CL2026
Environment Steering: Using Data Flow Control to Improve Agent Utility and Safety
Charlie Summers, Prajwal Raghunath, Aaditya Pai +4
LLM agents can make unsafe tool calls even when instructed to behave safely. Existing defenses constrain agents before execution, modify tool inputs/outputs, or rely on LLM judges;…
cs.DB2026
Data Flow Control: Data Safety Policies for AI Agents
Charlie Summers, Eugene Wu
Agents increasingly generate SQL, orchestrate pipelines, and automate data analysis on behalf of users. While recent work improves query correctness, correctness is not safety. A q…
cs.CR2025
Please Don't Kill My Vibe: Empowering Agents with Data Flow Control
Charlie Summers, Haneen Mohammed, Eugene Wu
The promise of Large Language Model (LLM) agents is to perform complex, stateful tasks. This promise is stunted by significant risks - policy violations, process corruption, and se…