6 citations · 9 across the 10 of their papers we have counts for
10 papers
Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras
Quanxin Zheng, Miao Fan, Shengtong Xu +2
Vectorized maps are indispensable for precise navigation and the safe operation of autonomous vehicles. Traditional methods for constructing these maps fall into two categories: of…
Improving SAM for Camouflaged Object Detection via Dual Stream Adapters
Jiaming Liu, Linghe Kong, Guihai Chen
Segment anything model (SAM) has shown impressive general-purpose segmentation performance on natural images, but its performance on camouflaged object detection (COD) is unsatisfa…
Pre-trained Molecular Language Models with Random Functional Group Masking
Tianhao Peng, Yuchen Li, Xuhong Li +7
Recent advancements in computational chemistry have leveraged the power of trans-former-based language models, such as MoLFormer, pre-trained using a vast amount of simplified mole…
Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)
Yuchen Li, Haoyi Xiong, Linghe Kong +4
Learning to rank (LTR) is widely employed in web searches to prioritize pertinent webpages from retrieved content based on input queries. However, traditional LTR models encounter…
Pre-trained Graphformer-based Ranking at Web-scale Search (Extended Abstract)
Yuchen Li, Haoyi Xiong, Linghe Kong +4
Both Transformer and Graph Neural Networks (GNNs) have been employed in the domain of learning to rank (LTR). However, these approaches adhere to two distinct yet complementary pro…
2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution
Kai Liu, Haotong Qin, Yong Guo +4
Low-bit quantization has become widespread for compressing image super-resolution (SR) models for edge deployment, which allows advanced SR models to enjoy compact low-bit paramete…
Binarized Diffusion Model for Image Super-Resolution
Zheng Chen, Haotong Qin, Yong Guo +4
Advanced diffusion models (DMs) perform impressively in image super-resolution (SR), but the high memory and computational costs hinder their deployment. Binarization, an ultra-com…
BinaryHPE: 3D Human Pose and Shape Estimation via Binarization
Zhiteng Li, Yulun Zhang, Jing Lin +5
3D human pose and shape estimation (HPE) aims to reconstruct the 3D human body, face, and hands from a single image. Although powerful deep learning models have achieved accurate e…
Image Super-Resolution with Text Prompt Diffusion
Zheng Chen, Yulun Zhang, Jinjin Gu +4
Image super-resolution (SR) methods typically model degradation to improve reconstruction accuracy in complex and unknown degradation scenarios. However, extracting degradation inf…
Natural Language based Context Modeling and Reasoning for Ubiquitous Computing with Large Language Models: A Tutorial
Haoyi Xiong, Jiang Bian, Sijia Yang +3
Large language models (LLMs) have become phenomenally surging, since 2018--two decades after introducing context-awareness into computing systems. Through taking into account the s…