The segmentation of kidney layer structures, including cortex, outer str...
Podocytes, specialized epithelial cells that envelop the glomerular
capi...
We consider the problem of sequential recommendation, where the current
...
Deep neural networks (DNNs) utilized recently are physically deployed wi...
Registration of distant outdoor LiDAR point clouds is crucial to extendi...
The Segment Anything Model (SAM) is a recently proposed prompt-based
seg...
Rapid developments in machine vision have led to advances in a variety o...
Multi-class cell segmentation in high-resolution Giga-pixel whole slide
...
Modeling multi-party conversations (MPCs) with graph neural networks has...
Zero-shot cross-lingual information extraction(IE) aims at constructing ...
Addressing the issues of who saying what to whom in multi-party conversa...
For many driving safety applications, it is of great importance to accur...
This paper describes the system developed by the USTC-NELSLIP team for
S...
The segment anything model (SAM) was released as a foundation model for ...
Monocular 3D object detection (Mono3D) in mobile settings (e.g., on a
ve...
Mobile monocular 3D object detection (Mono3D) (e.g., on a vehicle, a dro...
Zero-shot cross-lingual named entity recognition (NER) aims at transferr...
With the rapid development of self-supervised learning (e.g., contrastiv...
Comprehensive semantic segmentation on renal pathological images is
chal...
Learning individual-level treatment effect is a fundamental problem in c...
Multilingual BERT (mBERT), a language model pre-trained on large multili...
This paper describes the system developed by the USTC-NELSLIP team for
S...
Cross-language pre-trained models such as multilingual BERT (mBERT) have...
Advertisers play an essential role in many e-commerce platforms like Tao...
Computer-assisted quantitative analysis on Giga-pixel pathology images h...
The detection of ancient settlements is a key focus in landscape archaeo...
Digital advertising is a critical part of many e-commerce platforms such...
Personas are useful for dialogue response prediction. However, the perso...
Unsupervised learning algorithms (e.g., self-supervised learning,
auto-e...
Recent advances in bioimaging have provided scientists a superior high
s...
This paper introduces the SemEval-2021 shared task 4: Reading Comprehens...
Persona can function as the prior knowledge for maintaining the consiste...
Contrastive learning is a key technique of modern self-supervised learni...
Quantitative analysis of microscope videos often requires instance
segme...
Task-oriented conversational modeling with unstructured knowledge access...
We explore end-to-end trained differentiable models that integrate natur...
Instance object segmentation and tracking provide comprehensive
quantifi...
Weakly supervised learning has been rapidly advanced in biomedical image...
The unsupervised segmentation is an increasingly popular topic in biomed...
Performing fact verification based on structured data is important for m...
Recently, single-stage embedding based deep learning algorithms gain
inc...
The challenges of building knowledge-grounded retrieval-based chatbots l...
Disentanglement is a problem in which multiple conversations occur in th...
In this paper, we study the problem of employing pre-trained language mo...
The NOESIS II challenge, as the Track 2 of the 8th Dialogue System Techn...
We present our work on Track 4 in the Dialogue System Technology Challen...
This paper proposes an utterance-to-utterance interactive matching netwo...
This paper proposes a dually interactive matching network (DIM) for
pres...
Natural language inference (NLI) is among the most challenging tasks in
...
This paper proposes a new model, called condition-transforming variation...