REALISTA generates semantically coherent adversarial prompts via latent-space optimization over input-dependent editing directions, achieving stronger hallucination elicitation than prior realistic attacks on open-source and reasoning LLMs.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
Text captions of radio galaxy images can classify FR-I vs FR-II morphologies comparably to image embeddings, but LoRA fine-tuning improves local class coherence without improving global image-text alignment.
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REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations
REALISTA generates semantically coherent adversarial prompts via latent-space optimization over input-dependent editing directions, achieving stronger hallucination elicitation than prior realistic attacks on open-source and reasoning LLMs.
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Exploring Image-Text Alignment for Radio Galaxy Morphologies
Text captions of radio galaxy images can classify FR-I vs FR-II morphologies comparably to image embeddings, but LoRA fine-tuning improves local class coherence without improving global image-text alignment.