Papers by Maha Tufail Agro

2 papers
TrojanWave: Exploiting Prompt Learning for Stealthy Backdoor Attacks on Large Audio-Language Models (2025.emnlp-main)

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Challenge: Recent studies have shown that ALMs are vulnerable to adversarial attacks.
Approach: They propose a backdoor attack tailored to the prompt-learning setting in frozen audio-language models.
Outcome: The proposed method injects backdoors solely through learnable prompts, making it highly scalable and effective in few-shot settings.
Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Experts (2025.findings-acl)

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Challenge: Important efforts to characterize news media outlets in terms of their political bias and factuality are labor-intensive and prone to human biases.
Approach: They propose a method that emulates criteria used by professional fact-checkers to assess the factuality and political bias of an entire outlet.
Outcome: The proposed method improves on baselines and with multiple LLMs.

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