arXiv 2610.01496 · cs.CV · 2026-10-01
SALD: Self-Referenced Advantage Learning for Diffusion Models
Aryan Das, Surjo Dey, Koushik Biswas, Swalpa Kumar Roy, Moloud Abdar, Arnab Bhattacharya, Vinay Kumar Verma
Indian Institute of Technology, Kanpur
In latest · #225 Added on 2026-10-21
One-line takeaway
SALD lets a diffusion model score each image-caption pair at two noise levels, yielding self-referenced training signals without a teacher.
SALD 让扩散模型在两个噪声等级下自我对照打分，不需要教师模型就能获得训练信号。
Read on arXiv PDF Hugging Face discussion
Topics & disciplines
More on Visual generation
- MaLiang-Harness: A Programmable Path to Image and Video Generation ▲367
- Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation ▲364
- DiffusionART: Efficient, Stable and Scalable Reinforcement of Diffusion Models ▲325
- UltraText Bench: A Comprehensive Bilingual Benchmark for Evaluating Visual Text Rendering in Image Generation ▲197
- Matrix-Game 4.0: Harnessing Video Models for Real-Time Playable Game Worlds ▲182
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.