48 citations · 49 across the 4 of their papers we have counts for
6 papers
BELT : BEhavior-Aligned Low-Rank KV Cache Compression with Learned Top-k Rank Allocation
Yaoyang Liu, Shuwei Shen, Jincheng Tang +5
Long-context inference makes the key-value (KV) cache a major memory bottleneck for large language models. We propose BELT, a low-rank KV cache compression framework. Its key-side…
Calibrate the Decisions That Change the Future: On-Policy Post-Training Quantization for Multimodal Large Language Models
Wenxiao Fan, Jingling Fu, Lichen Ma +6
Post-training quantization (PTQ) lowers deployment cost for multimodal large language models, but calibration typically reconstructs fixed sequences with local objectives. This ove…
Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
Zhimin Li, Jianwei Zhang, Qin Lin +42
We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transfo…
Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent
Xiaonan Nie, Yi Liu, Fangcheng Fu +5
Recent years have witnessed the unprecedented achievements of large-scale pre-trained models, especially the Transformer models. Many products and services in Tencent Inc., such as…
M6: A Chinese Multimodal Pretrainer
Junyang Lin, Rui Men, An Yang +22
In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1.9TB images and 292GB texts that cover a wide range of domains. We pro…
A Multi-Semantic Metapath Model for Large Scale Heterogeneous Network Representation Learning
Xuandong Zhao, Jinbao Xue, Jin Yu +2
Network Embedding has been widely studied to model and manage data in a variety of real-world applications. However, most existing works focus on networks with single-typed nodes o…