Papers by Rana Shahroz

2 papers
Agents Under Siege: Breaking Pragmatic Multi-Agent LLM Systems with Optimized Prompt Attacks (2025.acl-long)

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Challenge: Multi-agent LLMs are prone to adversarial attacks because of constraints such as limited token bandwidth and latency between message delivery.
Approach: They propose a permutation-invariant adversarial attack that optimizes prompt distribution across latency and bandwidth constraints to bypass distributed safety mechanisms within the system.
Outcome: The proposed method outperforms conventional attacks by up to 7 on multiple models.
ORAL: Prompting Your Large-Scale LoRAs via Conditional Recurrent Diffusion (2025.findings-emnlp)

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Challenge: Existing approaches to low-rank Adaptation (LoRA) are limited in scalability and controllability.
Approach: They propose a conditional recurrent diffusion framework that generates LoRA parameters directly . they integrate model architecture and textual task specifications to generate task-specific parameters .
Outcome: The proposed framework scales to billions-of-parameter LLMs and maintains controllability.

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