This AI Paper from Tel Aviv University Introduces GASLITE: A Gradient-Based Method to Expose Vulnerabilities in Dense Embedding-Based Text Retrieval Systems

This AI Paper from Tel Aviv University Introduces GASLITE: A Gradient-Based Method to Expose Vulnerabilities in Dense Embedding-Based Text Retrieval Systems

Dense embedding-based text retrieval has become the cornerstone for ranking text passages in response to queries. The systems use deep learning models for embedding text into vector spaces that enable semantic similarity measurements. This method has been adopted widely in applications such as search engines and retrieval-augmented generation (RAG), where retrieving accurate and contextually relevant…

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This AI Paper from NVIDIA and SUTD Singapore Introduces TANGOFLUX and CRPO: Efficient and High-Quality Text-to-Audio Generation with Flow Matching

This AI Paper from NVIDIA and SUTD Singapore Introduces TANGOFLUX and CRPO: Efficient and High-Quality Text-to-Audio Generation with Flow Matching

Text-to-audio generation has transformed how audio content is created, automating processes that traditionally required significant expertise and time. This technology enables the conversion of textual prompts into diverse and expressive audio, streamlining workflows in audio production and creative industries. Bridging textual input with realistic audio outputs has opened possibilities in applications like multimedia storytelling, music,…

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