In recent years, there have been remarkable advancements in the performa...
Cross-lingual named entity recognition (CrossNER) faces challenges stemm...
As the size of transformer-based models continues to grow, fine-tuning t...
We investigate various prompting strategies for enhancing personalized
r...
Face recognition is a widely-used technique for identification or
verifi...
Large language models show impressive results on few-shot NLP tasks. How...
This paper introduces the Fair Fairness Benchmark (), a
benchmarking fra...
The past decade has witnessed the flourishing of a new profession as med...
Chain-of-Thought prompting (CoT) enables large-scale language models to ...
Chinese Spelling Correction (CSC) aims to detect and correct erroneous
c...
We propose attribute-aware multimodal entity linking, where the input is...
Contrastively trained vision-language models have achieved remarkable
pr...
Decision tree (DT) is a widely used machine learning model due to its
ve...
Optical flow is an indispensable building block for various important
co...
Recently, self-supervised learning (SSL) was shown to be vulnerable to
p...
Whether by processing videos with fixed resolution from start to end or
...
Named entity recognition (NER) is an important research problem in natur...
Federated learning is a distributed learning framework that takes full
a...
Masked Language Modeling (MLM) has been one of the most prominent approa...
Instance segmentation in videos, which aims to segment and track multipl...
Predicting personality traits based on online posts has emerged as an
im...
Active learning with strong and weak labelers considers a practical sett...
Personalized text generation has broad industrial applications, such as
...
Fine-tuning large pre-trained language models on downstream tasks is apt...
Transformer-based models have achieved great success on sentence pair
mo...
Prompt tuning learns soft prompts to condition frozen Pre-trained Langua...
Task-oriented dialog (TOD) systems often require interaction with an ext...
Pre-trained Language Models (PLMs) have achieved remarkable performance ...
Fall detection for the elderly is a well-researched problem with several...
Facial pose estimation refers to the task of predicting face orientation...
Driven by the teacher-student paradigm, knowledge distillation is one of...
Video captioning is a challenging task as it needs to accurately transfo...
Network embedding is an effective technique to learn the low-dimensional...
The classification service over a stream of data is becoming an importan...
Structure information extraction refers to the task of extracting struct...
Recent studies on Graph Convolutional Networks (GCNs) reveal that the in...
Transformers-based models, such as BERT, have been one of the most succe...
The latest advance in recommendation shows that better user and item
rep...