AINewsnow

Controllable Diverse Sampling through Pullback Directions

arXiv:2610.14294v1 Announce Type: new Abstract: Conditional diffusion models can generate high-quality images that align closely with a given prompt. However, samples generated from different random seeds may remain visually similar, limiting creative exploration. Existing approaches can increase v…

Read the full story at arXiv cs.AI ↗

Timeline · 1 report

  1. 2026-10-15 04:00 · arXiv cs.AI
    Controllable Diverse Sampling through Pullback Directions

More stories

  1. OpenAI engineer charged with planting surveillance device in office — Sky News Technology
  2. Anthropic reports $16.8 billion Q3 revenue ahead of planned IPO — Bloomberg AI
  3. Eight US states sue OpenAI over alleged safety risks to children — The Verge AI
  4. MIT Professor Explores AI's Impact on Thinking Skills in New Book — MIT News AI
  5. SK Hynix and Samsung shares plunge amid tech sell-off — CNBC Technology
  6. Figma introduces agent features and open beta for code layers — TechCrunch AI
  7. Meta Study: Most Small Businesses Use AI for Productivity — Meta Newsroom
  8. Google and Meta launch new frontier AI models amid competitive benchmarking — Google Gemini Blog

Get the daily brief of stories like this at 6:30 every morning →