Recruitpro: A pretrained language model with skill-aware prompt learning for intelligent recruitment
Recent years have witnessed the rapid development of machine-learning-based intelligent
recruitment services. Along this line, a large number of emerging models have been …
recruitment services. Along this line, a large number of emerging models have been …
Towards global video scene segmentation with context-aware transformer
Videos such as movies or TV episodes usually need to divide the long storyline into
cohesive units, ie, scenes, to facilitate the understanding of video semantics. The key …
cohesive units, ie, scenes, to facilitate the understanding of video semantics. The key …
Facilitating multimodal classification via dynamically learning modality gap
Multimodal learning falls into the trap of the optimization dilemma due to the modality
imbalance phenomenon, leading to unsatisfactory performance in real applications. A core …
imbalance phenomenon, leading to unsatisfactory performance in real applications. A core …
Self-weighted contrastive learning among multiple views for mitigating representation degeneration
Recently, numerous studies have demonstrated the effectiveness of contrastive learning
(CL), which learns feature representations by pulling in positive samples while pushing …
(CL), which learns feature representations by pulling in positive samples while pushing …
Contextualized knowledge graph embedding for explainable talent training course recommendation
Learning and development, or L&D, plays an important role in talent management, which
aims to improve the knowledge and capabilities of employees through a variety of …
aims to improve the knowledge and capabilities of employees through a variety of …
Covlr: Coordinating cross-modal consistency and intra-modal relations for vision-language retrieval
Vision-language retrieval aims to perform cross-modal instances search by learning
consistent vision-language representations. However, in real applications, vision-language …
consistent vision-language representations. However, in real applications, vision-language …
Resuformer: Semantic structure understanding for resumes via multi-modal pre-training
Understanding the semantic structure of resumes plays an important role for various
intelligent recruitment related applications. However, due to the unique characteristics of …
intelligent recruitment related applications. However, due to the unique characteristics of …
Semantic-guided adversarial diffusion model for self-supervised shadow removal
Existing unsupervised methods have addressed the challenges of inconsistent paired data
and tedious acquisition of ground-truth labels in shadow removal tasks. However, GAN …
and tedious acquisition of ground-truth labels in shadow removal tasks. However, GAN …
Learning to Rebalance Multi-Modal Optimization by Adaptively Masking Subnetworks
Multi-modal learning aims to enhance performance by unifying models from various
modalities but often faces the" modality imbalance" problem in real data, leading to a bias …
modalities but often faces the" modality imbalance" problem in real data, leading to a bias …
Multimodal Classification via Modal-Aware Interactive Enhancement
Due to the notorious modality imbalance problem, multimodal learning (MML) leads to the
phenomenon of optimization imbalance, thus struggling to achieve satisfactory performance …
phenomenon of optimization imbalance, thus struggling to achieve satisfactory performance …