Current cross-prompt automated essay scoring (AES) is a challenging task due to the large
discrepancies between different prompts, such as different genres and expressions. The …

Cross-lingual named entity recognition (CrossNER) faces challenges stemming from
uneven performance due to the scarcity of multilingual corpora, especially for non-English …

WiFi channel state information (CSI)-based activity recognition has sparked numerous
studies due to its widespread availability and privacy protection. However, when applied in …

Chinese diachronic gap is a key issue in classical Chinese machine reading
comprehension (CCMRC). Preceding work on bridging this gap has been mostly restricted …

Previous license plate recognition (LPR) methods have achieved impressive performance
on single-type license plates. However, multi-type license plate recognition is still …

Recent studies tend to employ Contrastive Learning (CL) methods to facilitate model training
by extracting self-supervised signals to mitigate data sparsity. However, existing CL-based …

The considerable semantic information contained in multimodal data is increasingly
appreciated by industry and academia. To effectively leverage multimodal information …

Current cross-prompt automatic essay scoring (AES) systems are primarily concerned with
obtaining shared knowledge specific to the target prompt by using the source and target …

Benefiting many information retrieval applications, named entity recognition (NER) has
shown impressive progress. Recently, there has been a growing trend to decompose …

Unsupervised cross-lingual transfer involves transferring knowledge between languages
without explicit supervision. Although numerous studies have been conducted to improve …