Visual Grounding (VG) is a crucial topic in the field of vision and language, which involves
locating a specific region described by expressions within an image. To reduce the reliance …

Few-shot relation classification (FSRC) focuses on recognizing novel relations by learning
with merely a handful of annotated instances. Meta-learning has been widely adopted for …

Training a deep-learning text classification model usually requires a large amount of labeled
data, yet labeling data are usually labor-intensive and time-consuming. Few-shot text …

While Chain of Thought (CoT) prompting approaches have significantly consolidated the
reasoning capabilities of large language models (LLMs), they still face limitations that …

Deep learning has demonstrated great potential in the field of gas recognition using an
electronic nose. However, owing to the limited resources of embedded devices, they can …

Unsupervised cross-lingual transfer has been shown great potentials for dependency
parsing of the low-resource languages when there is no annotated treebank available …

Since deep learning is the dominant paradigm in the multi-turn dialogue generation task,
large-scale training data is the key factor affecting the model performance. To make full use …

Sequential prediction has great value for resource allocation due to its capability in
analyzing intents for next prediction. A fundamental challenge arises from real-world …

Anomaly detection in multivariate time series (MVTS) is a significant research domain across
several industries, including cybersecurity and industrial systems. There have been several …

Assessing response quality to instructions in language models is vital but challenging due to
the complexity of human language across different contexts. This complexity often results in …