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DiSCO: Defending text-to-image generation through distribution-guided contrastiv
BACKGROUND
1 SIGNALFIRST DETECTED 19 August 2026
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19 Aug
DiSCO: Defending text-to-image generation through distribution-guided contrastive prompt optimization
REPORT · WHAT · ArXiv CS.AI
Other feeds and industry voices
20 Mar
A Concept is More Than a Word: Diversified Unlearning in Text-to-Image Diffusion Models
arXiv:2603.18767v1 Announce Type: new Abstract: Concept unlearning has emerged as a promising direction for reducing the risks of harmful content generation in text-to-image
REPORT · WHAT · ArXiv CS.AIOPEN STORY
25 Mar
Efficient Embedding-based Synthetic Data Generation for Complex Reasoning Tasks
arXiv:2603.22294v1 Announce Type: cross Abstract: Synthetic Data Generation (SDG), leveraging Large Language Models (LLMs), has recently been recognized and broadly adopted as an
REPORT · WHAT · ArXiv CS.AIOPEN STORY
20 Mar
Soft-Di[M]O: Improving One-Step Discrete Image Generation with Soft Embeddings
arXiv:2509.22925v2 Announce Type: replace-cross Abstract: One-step generators distilled from Masked Diffusion Models (MDMs) compress multiple sampling steps into a single forward
REPORT · WHAT · ArXiv CS.AIOPEN STORY
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