ASB is a new benchmark that tests 10 prompt injection attacks, memory poisoning, a novel Plan-of-Thought backdoor attack, and 11 defenses on LLM agents across 13 models, finding attack success rates up to 84.3% and limited defense effectiveness.
u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt\
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RGoT uses RL to adaptively generate task-specific graphs of operations for GoT-style LLM prompting from a human-provided set, with results suggesting feasibility under constraints.
citing papers explorer
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Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents
ASB is a new benchmark that tests 10 prompt injection attacks, memory poisoning, a novel Plan-of-Thought backdoor attack, and 11 defenses on LLM agents across 13 models, finding attack success rates up to 84.3% and limited defense effectiveness.
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Reinforced Graph of Thoughts: RL-Driven Adaptive Prompting for LLMs
RGoT uses RL to adaptively generate task-specific graphs of operations for GoT-style LLM prompting from a human-provided set, with results suggesting feasibility under constraints.