ESLD extracts safety signals directly from the latent space of any guard model to enable faster and more accurate prompt-injection detection without retraining.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
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ORPHEAS, a Greek-English embedding model created with knowledge graph fine-tuning, outperforms state-of-the-art multilingual models on monolingual and cross-lingual retrieval benchmarks.
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ESLD (External Surrogate Latent Defense): A Latent-Space Architecture for Faster, Stronger Prompt-Injection Defense
ESLD extracts safety signals directly from the latent space of any guard model to enable faster and more accurate prompt-injection detection without retraining.
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ORPHEAS: A Cross-Lingual Greek-English Embedding Model for Retrieval-Augmented Generation
ORPHEAS, a Greek-English embedding model created with knowledge graph fine-tuning, outperforms state-of-the-art multilingual models on monolingual and cross-lingual retrieval benchmarks.