Papers by Zaber Ibn Abdul Hakim

2 papers
SteerVLM: Robust Model Control through Lightweight Activation Steering for Vision Language Models (2025.findings-emnlp)

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Challenge: SteerVLM is a lightweight steering module designed to guide Vision-Language Models (VLMs) towards outputs that better adhere to desired instructions.
Approach: They propose a lightweight steering module that learns from latent embeddings of paired prompts encoding target and converse behaviors to dynamically adjust activations connecting the language modality with image context.
Outcome: The proposed steering module outperforms existing intervention techniques on steering and hallucination mitigation benchmarks for VLMs.
SoundBreak: A Systematic Study of Audio-Only Adversarial Attacks on Trimodal Models (2026.acl-long)

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Challenge: Recent advances in multimodal large language models have increased their vulnerability to adversarial manipulation.
Approach: They propose to target audio-only adversarial attacks on multimodal audio–video–language models . they show that attacks can be successful at low perceptual distortions .
Outcome: The proposed models achieve up to 96% success rate under realistic conditions . the proposed models are more robust to noise than to noise and distortion than to speech recognition systems .

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