BenchJack audits 10 AI agent benchmarks, synthesizes exploits achieving near-perfect scores without task completion, surfaces 219 flaws, and reduces hackable-task ratios to under 10% on four benchmarks via iterative patching.
Netpress: Dynamically generated llm benchmarks for network applications
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
A case study with 105 network engineers found that an LLM chatbot with RAG, CLI control, and ticket access received positive evaluations in 68.1% of interactions while assisting with building and operating a large demonstration network.
citing papers explorer
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Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack
BenchJack audits 10 AI agent benchmarks, synthesizes exploits achieving near-perfect scores without task completion, surfaces 219 flaws, and reduces hackable-task ratios to under 10% on four benchmarks via iterative patching.
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How Helpful is LLM Assistance in Network Operations? A Case Study at a Large Demonstration Network
A case study with 105 network engineers found that an LLM chatbot with RAG, CLI control, and ticket access received positive evaluations in 68.1% of interactions while assisting with building and operating a large demonstration network.