Looped Diffusion Transformer
Looped-DiT reuses shared Transformer blocks within each denoising step, letting a 260M-parameter text-to-image model beat one 6.5x larger at 4.9x lower compute.
Stories per day · 30 days
4 stories, newest first · one card per story
Stories tagged #efficient-inference
When2Think: Learning Difficulty-Aware Length Control for Efficient Hybrid Reasoning Models
When2Think post-training framework allocates reasoning depth by problem difficulty, raising AIME24 Pass@3 10.0% while cutting token usage 27.9%.
MoME: Mixture-of-Memory Embeddings for Context-Aware Sparse Lookup
MoME introduces context-aware memory embeddings with gated multi-slot lookup, improving LLM efficiency across Llama-3 and Qwen3 backbones.
ReactVAU: A Slow-Fast Decoupled Framework for Streaming Video Anomaly Understanding
ReactVAU is a slow-fast streaming framework for real-time video anomaly understanding that reserves heavyweight MLLM reasoning for suspicious events, improving efficiency.