AcFlow: Controlling Text-to-Image Diffusion Transformers via Learned Conditional Activation Flow
This story is from 2026-09-11. It is preserved in the archive; the latest stories are on the live feed.
arXiv:2609.10723v1 Announce Type: new Abstract: Text-to-image diffusion transformers (DiTs) are powerful generators, yet direct prompting provides limited control interface for style intensity and can fail to suppress unwanted concepts. To enable these controls, we introduce AcFlow, an inference-ti…
Read the full story at arXiv cs.CV ↗
Timeline · 1 report
- 2026-09-11 04:00 · arXiv cs.CV
AcFlow: Controlling Text-to-Image Diffusion Transformers via Learned Conditional Activation Flow
More stories
- Anthropic says Claude 'leads' 26 percent of its AI R&D work — Engadget
- Google Joins OpenAI, Anthropic, Meta in Disclosing AI Hacks — Bloomberg AI
- Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
- Optimizing agent system prompts with Amazon Bedrock AgentCore — AWS Machine Learning Blog
- Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
- Introducing Astra for Law — OpenAI News
- Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
- OpenAI reveals cases of ‘concerning’ AI behaviour as it announces new disclosure system — The Guardian AI
Get the daily brief of stories like this at 6:30 every morning →