15 citations · 54 across the 19 of their papers we have counts for
19 papers
What a Pooled Leaderboard Does Not Say: Auditing the Scope and Provenance of Method Comparisons in Microservice RCA Benchmarks
Lining Hu, Ting Liu, Yuzhuo Fu
Offline benchmarks for microservice root cause analysis (RCA) rank methods by a score pooled over several applications, and a pooled lead leaves two things unstated: on which of th…
Understanding Robustness of Parameter-Efficient Tuning for Image Classification
Jiacheng Ruan, Xian Gao, Suncheng Xiang +3
Parameter-efficient tuning (PET) techniques calibrate the model's predictions on downstream tasks by freezing the pre-trained models and introducing a small number of learnable par…
MM-CamObj: A Comprehensive Multimodal Dataset for Camouflaged Object Scenarios
Jiacheng Ruan, Wenzhen Yuan, Zehao Lin +5
Large visual-language models (LVLMs) have achieved great success in multiple applications. However, they still encounter challenges in complex scenes, especially those involving ca…
iDAT: inverse Distillation Adapter-Tuning
Jiacheng Ruan, Jingsheng Gao, Mingye Xie +4
Adapter-Tuning (AT) method involves freezing a pre-trained model and introducing trainable adapter modules to acquire downstream knowledge, thereby calibrating the model for better…
Oceanship: A Large-Scale Dataset for Underwater Audio Target Recognition
Zeyu Li, Suncheng Xiang, Tong Yu +5
The recognition of underwater audio plays a significant role in identifying a vessel while it is in motion. Underwater target recognition tasks have a wide range of applications in…
LAMM: Label Alignment for Multi-Modal Prompt Learning
Jingsheng Gao, Jiacheng Ruan, Suncheng Xiang +5
With the success of pre-trained visual-language (VL) models such as CLIP in visual representation tasks, transferring pre-trained models to downstream tasks has become a crucial pa…
GIST: Improving Parameter Efficient Fine Tuning via Knowledge Interaction
Jiacheng Ruan, Jingsheng Gao, Mingye Xie +4
The Parameter-Efficient Fine-Tuning (PEFT) method, which adjusts or introduces fewer trainable parameters to calibrate pre-trained models on downstream tasks, has become a recent r…
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation
Jiacheng Ruan, Mingye Xie, Jingsheng Gao +2
Transformer and its variants have been widely used for medical image segmentation. However, the large number of parameter and computational load of these models make them unsuitabl…
LiveChat: A Large-Scale Personalized Dialogue Dataset Automatically Constructed from Live Streaming
Jingsheng Gao, Yixin Lian, Ziyi Zhou +2
Open-domain dialogue systems have made promising progress in recent years. While the state-of-the-art dialogue agents are built upon large-scale text-based social media data and la…
Learning Robust Visual-Semantic Embedding for Generalizable Person Re-identification
Suncheng Xiang, Jingsheng Gao, Mengyuan Guan +5
Generalizable person re-identification (Re-ID) is a very hot research topic in machine learning and computer vision, which plays a significant role in realistic scenarios due to it…
CluCDD:Contrastive Dialogue Disentanglement via Clustering
Jingsheng Gao, Zeyu Li, Suncheng Xiang +2
A huge number of multi-participant dialogues happen online every day, which leads to difficulty in understanding the nature of dialogue dynamics for both humans and machines. Dialo…
Deep Multimodal Fusion for Generalizable Person Re-identification
Suncheng Xiang, Hao Chen, Wei Ran +4
Person re-identification plays a significant role in realistic scenarios due to its various applications in public security and video surveillance. Recently, leveraging the supervi…
MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion Segmentation
Jiacheng Ruan, Suncheng Xiang, Mingye Xie +2
Recently, some pioneering works have preferred applying more complex modules to improve segmentation performances. However, it is not friendly for actual clinical environments due…
MEW-UNet: Multi-axis representation learning in frequency domain for medical image segmentation
Jiacheng Ruan, Mingye Xie, Suncheng Xiang +2
Recently, Visual Transformer (ViT) has been widely used in various fields of computer vision due to applying self-attention mechanism in the spatial domain to modeling global knowl…
Rethinking Person Re-Identification via Semantic-Based Pretraining
Suncheng Xiang, Jingsheng Gao, Zirui Zhang +5
Pretraining is a dominant paradigm in computer vision. Generally, supervised ImageNet pretraining is commonly used to initialize the backbones of person re-identification (Re-ID) m…
Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification
Suncheng Xiang, Guanjie You, Mengyuan Guan +4
Person re-identification (re-ID) plays an important role in applications such as public security and video surveillance. Recently, learning from synthetic data, which benefits from…
Learning from Self-Discrepancy via Multiple Co-teaching for Cross-Domain Person Re-Identification
Suncheng Xiang, Yuzhuo Fu, Mengyuan Guan +1
Employing clustering strategy to assign unlabeled target images with pseudo labels has become a trend for person re-identification (re-ID) algorithms in domain adaptation. A potent…
Taking A Closer Look at Synthesis: Fine-grained Attribute Analysis for Person Re-Identification
Suncheng Xiang, Yuzhuo Fu, Guanjie You +1
Person re-identification (re-ID) plays an important role in applications such as public security and video surveillance. Recently, learning from synthetic data, which benefits from…
Attribute analysis with synthetic dataset for person re-identification
Suncheng Xiang, Yuzhuo Fu, Guanjie You +1
Person re-identification (re-ID) plays an important role in applications such as public security and video surveillance. Recently, learning from synthetic data, which benefits from…