1.8k citations · 3.8k across the 131 of their papers we have counts for
10 papers · 1 filter
MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices
Xiangxiang Chu, Limeng Qiao, Xinyang Lin +8
We present MobileVLM, a competent multimodal vision language model (MMVLM) targeted to run on mobile devices. It is an amalgamation of a myriad of architectural designs and techniq…
Lenna: Language Enhanced Reasoning Detection Assistant
Fei Wei, Xinyu Zhang, Ailing Zhang +2
With the fast-paced development of multimodal large language models (MLLMs), we can now converse with AI systems in natural languages to understand images. However, the reasoning p…
RobustCalib: Robust Lidar-Camera Extrinsic Calibration with Consistency Learning
Shuang Xu, Sifan Zhou, Zhi Tian +3
Current traditional methods for LiDAR-camera extrinsics estimation depend on offline targets and human efforts, while learning-based approaches resort to iterative refinement for c…
A Speed Odyssey for Deployable Quantization of LLMs
Qingyuan Li, Ran Meng, Yiduo Li +6
The large language model era urges faster and less costly inference. Prior model compression works on LLMs tend to undertake a software-centric approach primarily focused on the si…
Robust MAE-Driven NAS: From Mask Reconstruction to Architecture Innovation
Yiming Hu, Xiangxiang Chu, Yong Wang
Neural Architecture Search (NAS) relies heavily on labeled data, which is labor-intensive and time-consuming to obtain. In this paper, we propose a novel NAS method based on an uns…
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models
Liang Li, Qingyuan Li, Bo Zhang +1
As the size of large language models (LLMs) continues to grow, model compression without sacrificing accuracy has become a crucial challenge for deployment. While some quantization…
FPTQ: Fine-grained Post-Training Quantization for Large Language Models
Qingyuan Li, Yifan Zhang, Liang Li +6
In the era of large-scale language models, the substantial parameter size poses significant challenges for deployment. Being a prevalent compression technique, quantization has eme…
FastPillars: A Deployment-friendly Pillar-based 3D Detector
Sifan Zhou, Zhi Tian, Xiangxiang Chu +7
The deployment of 3D detectors strikes one of the major challenges in real-world self-driving scenarios. Existing BEV-based (i.e., Bird Eye View) detectors favor sparse convolution…
EfficientRep:An Efficient Repvgg-style ConvNets with Hardware-aware Neural Network Design
Kaiheng Weng, Xiangxiang Chu, Xiaoming Xu +2
We present a hardware-efficient architecture of convolutional neural network, which has a repvgg-like architecture. Flops or parameters are traditional metrics to evaluate the effi…
YOLOv6 v3.0: A Full-Scale Reloading
Chuyi Li, Lulu Li, Yifei Geng +6
The YOLO community has been in high spirits since our first two releases! By the advent of Chinese New Year 2023, which sees the Year of the Rabbit, we refurnish YOLOv6 with numero…