Papers by Chaim Baskin

2 papers
CARES: Context-Aware Resolution Selector for VLMs (2026.acl-long)

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Challenge: Large vision–language models process images at native or high resolution to remain effective across tasks.
Approach: They propose a lightweight preprocessing module that predicts the minimum sufficient input resolution for large vision–language models.
Outcome: CARES predicts when a pre-trained VLM's response converges to its peak ability to answer correctly, reducing compute by up to 80%.
Jailbreak Attack Initializations as Extractors of Compliance Directions (2025.findings-emnlp)

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Challenge: Safety-aligned LLMs respond to prompts with compliance or refusal, each corresponding to distinct directions in the model’s activation space.
Approach: They propose an initialization framework that aims to project unseen prompts further along compliance directions.
Outcome: The proposed initialization framework achieves an increased attack success rate and reduced computational overhead, highlighting the fragility of safety-aligned LLMs.

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