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20232026
most citedPast-Future Scheduler for LLM Serving under SLA Guarantees

10 citations · 29 across the 15 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

DreamHMR: From Video Generation to Human Motion Modeling via Structural Focusing

Zhengjie Xu, Ruihao Gong, Xianglong Liu

Human mesh recovery (HMR) provides a geometric foundation for understanding human motion, but accurately reconstructing both body motion and fine hand articulation from videos rema…

cs.CV2026

LightVAE: Towards Compact and Efficient Video Autoencoders

Shiqiao Gu, Yang Yong, Fengjun Zhong +5

Latent diffusion models enable high-quality video generation, but video VAE encoding and decoding remain computationally expensive. Existing methods use stage-specific lightweight…

cs.CV2026

Collaborative Few-Step Distillation and Low-Bit Quantization for Wan2.2 Dual-Expert Video Diffusion Models

Jinyang Du, Shenghao Jin, Ziqian Xu +5

Large video diffusion models achieve strong visual quality but remain expensive to deploy because each sample requires many denoising steps and a large resident parameter footprint…

cs.DC2026

DisagFusion: Asynchronous Pipeline Parallelism and Elastic Scheduling for Disaggregated Diffusion Serving

Hantian Zha, Teng Ma, Yang Yong +7

Diffusion-based generation is increasingly powering production content pipelines; however, deploying these models at scale remains a significant challenge. Model weights frequently…

cs.CV2026

QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks

Haotong Qin, Xudong Ma, Xianglong Liu +4

Low-bit quantization is widely used to compress super-resolution (SR) models and reduce storage and computation costs for deployment on resource-limited devices. However, when SR m…

cs.RO2026

Advances and Innovations in the Multi-Agent Robotic System (MARS) Challenge

Li Kang, Heng Zhou, Xiufeng Song +41

Recent advancements in multimodal large language models and vision-languageaction models have significantly driven progress in Embodied AI. As the field transitions toward more com…