5 papers
HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds
Team HY-World, Chenjie Cao, Xuhui Zuo +42
We introduce HY-World 2.0, a multi-modal world model framework that advances our prior project HY-World 1.0. HY-World 2.0 accommodates diverse input modalities, including text prom…
AngelSlim: A more accessible, comprehensive, and efficient toolkit for large model compression
Rui Cen, QiangQiang Hu, Hong Huang +10
This technical report introduces AngelSlim, a comprehensive and versatile toolkit for large model compression developed by the Tencent Hunyuan team. By consolidating cutting-edge a…
DAQ: Delta-Aware Quantization for Post-Training LLM Weight Compression
Xiaoming Yu, Shize Tang, Guanghua Yu +4
We introduce Delta-Aware Quantization (DAQ), a data-free post-training quantization framework that preserves the knowledge acquired during post-training. Standard quantization obje…
IDPruner: Harmonizing Importance and Diversity in Visual Token Pruning for MLLMs
Yifan Tan, Yifu Sun, Shirui Huang +4
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities, yet they encounter significant computational bottlenecks due to the massive volume of visual tok…
Sherry: Hardware-Efficient 1.25-Bit Ternary Quantization via Fine-grained Sparsification
Hong Huang, Decheng Wu, Qiangqiang Hu +5
The deployment of Large Language Models (LLMs) on resource-constrained edge devices is increasingly hindered by prohibitive memory and computational requirements. While ternary qua…