Object detection is a crucial component of autonomous driving, and many
...
Artificial intelligence has been applied in various aspects of online
ed...
In recent research, slight performance improvement is observed from auto...
The scale of large pre-trained models (PTMs) poses significant challenge...
The unprecedented performance of large language models (LLMs) necessitat...
Parameter-efficient tuning (PET) methods can effectively drive extremely...
The recent upsurge in pre-trained large models (e.g. GPT-4) has swept ac...
Consistently scaling pre-trained language models (PLMs) imposes substant...
Fine-tuning on instruction data has been widely validated as an effectiv...
The ability to automatically detect and track surgical instruments in
en...
Object detection (OD) is crucial to autonomous driving. Unknown objects ...
Long-form question answering (LFQA) aims at answering complex, open-ende...
The application of visual tracking to the performance analysis of sports...
Humans possess an extraordinary ability to create and utilize tools, all...
This paper presents a novel method for depth completion, which leverages...
Although industrial anomaly detection (AD) technology has made significa...
With the evergrowing sizes of pre-trained models (PTMs), it has been an
...
The diverse relationships among real-world events, including coreference...
Metric-based meta-learning is one of the de facto standards in few-shot
...
A lack of driver's vigilance is the main cause of most vehicle crashes.
...
Delta tuning (DET, also known as parameter-efficient tuning) is deemed a...
Adapting large pre-trained models (PTMs) through fine-tuning imposes
pro...
To understand human behaviors, action recognition based on videos is a c...
Domain Adaptation aims to transfer the knowledge learned from a labeled
...
Prompt-based tuning for pre-trained language models (PLMs) has shown its...
Prompt-learning has become a new paradigm in modern natural language
pro...
How can pre-trained language models (PLMs) learn universal representatio...
As an effective approach to tune pre-trained language models (PLMs) for
...
Tuning pre-trained language models (PLMs) with task-specific prompts has...
A hopping leg, no matter in legged animals or humans, usually behaves li...
As a kind of generative self-supervised learning methods, generative
adv...
Despite pre-trained language models have proven useful for learning
high...
Fine-tuned pre-trained language models (PLMs) have achieved awesome
perf...
Recently, considerable literature has grown up around the theme of few-s...
This paper describes our submission for the End-to-end Multi-domain Task...
Deep neural models have hitherto achieved significant performances on
nu...
This paper proposes a novel deep convolutional model, Tri-Points Based L...
The last decade has witnessed remarkable progress in the image captionin...
Fully supervised neural approaches have achieved significant progress in...
In this paper we present DELTA, a deep learning based language technolog...
The basis of generating secret key from the common wireless channel at t...