In the rapidly evolving field of large language models (LLMs), data augmentation (DA) has
emerged as a pivotal technique for enhancing model performance by diversifying training …

Crop management plays a crucial role in determining crop yield economic profitability and
environmental sustainability. Despite the availability of management guidelines optimizing …

Data annotation and synthesis generally refers to the labeling or generating of raw data with
relevant information, which could be used for improving the efficacy of machine learning …

Large Language Models (LLMs) have revolutionized the fields of computer vision (CV) and
natural language processing (NLP). One of the most notable advancements of LLMs is that a …

Abstract Temporal Knowledge Graph Reasoning (TKGR) is the process of utilizing temporal
information to capture complex relations within a Temporal Knowledge Graph (TKG) to infer …

Social media platforms are hubs for multimodal information exchange, encompassing text,
images, and videos, making it challenging for machines to comprehend the information or …

Graphs play an important role in representing complex relationships in various domains like
social networks, knowledge graphs, and molecular discovery. With the advent of deep …

Large language models (LLMs) have reached human-like proficiency in generating diverse
textual content, underscoring the necessity for effective fake text detection to avoid potential …

Large language models (LLMs), while exhibiting exceptional performance, suffer from
hallucinations, especially on knowledge-intensive tasks. Existing works propose to augment …

Accurate stock market predictions following earnings reports are crucial for investors.
Traditional methods, particularly classical machine learning models, struggle with these …