most citedRethinking the Privacy of Text Embeddings: A Reproducibility Study of "Text Embeddings Reveal (Almost) As Much As Text"

2 citations · 2 across the 1 of their papers we have counts for

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2 papers

cs.CL2025★ 2 cited

Rethinking the Privacy of Text Embeddings: A Reproducibility Study of "Text Embeddings Reveal (Almost) As Much As Text"

Dominykas Seputis, Yongkang Li, Karsten Langerak +1

Text embeddings are fundamental to many natural language processing (NLP) tasks, extensively applied in domains such as recommendation systems and information retrieval (IR). Tradi…

cs.CV2024

Multi-Modal Adapter for Vision-Language Models

Dominykas Seputis, Serghei Mihailov, Soham Chatterjee +1

Large pre-trained vision-language models, such as CLIP, have demonstrated state-of-the-art performance across a wide range of image classification tasks, without requiring retraini…