1 citations · 1 across the 4 of their papers we have counts for
4 papers
Delta Decompression for MoE-based LLMs Compression
Hao Gu, Wei Li, Lujun Li +5
Mixture-of-Experts (MoE) architectures in large language models (LLMs) achieve exceptional performance, but face prohibitive storage and memory requirements. To address these chall…
Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis
Zhen Ye, Xinfa Zhu, Chi-Min Chan +17
Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and i…
Every Angle Is Worth A Second Glance: Mining Kinematic Skeletal Structures from Multi-view Joint Cloud
Junkun Jiang, Jie Chen, Ho Yin Au +3
Multi-person motion capture over sparse angular observations is a challenging problem under interference from both self- and mutual-occlusions. Existing works produce accurate 2D j…
HiPrompt: Tuning-free Higher-Resolution Generation with Hierarchical MLLM Prompts
Xinyu Liu, Yingqing He, Lanqing Guo +10
The potential for higher-resolution image generation using pretrained diffusion models is immense, yet these models often struggle with issues of object repetition and structural a…