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#sampling-optimization News & Analysis

2 articles tagged with #sampling-optimization. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AINeutralarXiv – CS AI · Jun 26/10
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InFerActive: Interactive Tree-Based Exploration of LLM Sampling for Safety Evaluation

InFerActive is an interactive system that improves how AI safety evaluators assess large language models by visualizing sampling results as navigable trees rather than static spreadsheets. The tool uses breadth-first sampling to achieve equivalent harmful-response coverage with up to 5x fewer samples, significantly improving evaluation efficiency according to controlled user studies.

AINeutralarXiv – CS AI · May 276/10
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CFG-OEC: Classifier Free Guidance with Orthogonal Error Correction

Researchers propose CFG-OEC, an improvement to classifier-free guidance in diffusion models that corrects structural sampling errors caused by misalignment between training objectives and sampling procedures. The method demonstrates improved image generation quality on Stable Diffusion models, achieving better FID and CLIP scores than existing approaches.

🧠 Stable Diffusion