Yichen Liu

Decoupling Deep Domain Adaptation Method for Class-imbalanced Learning with Domain Discrepancy

2021 · 2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)

In a wide range of classification tasks, training data will produce class-imbalance due to collection difficulties in some classes, which leads to prediction biases on minority classes. For the class-imbalanced problem, existing researches are usually …

LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context Scenarios

2024 · arXiv (Cornell University)

As Large Language Models (LLMs) evolve in natural language processing (NLP), their ability to stably follow instructions in long-context inputs has become critical for real-world applications. However, existing benchmarks seldom focus on instruction-following in long-context …

Grid Financial Data Enhancement and Anomaly Detection Based on Generative Adversarial Network Driving

2025

With the increasing business complexity and digitisation of financial systems in power grid enterprises, financial data presents high dimensionality, imbalance, noise and other characteristics, which brings serious challenges to data analysis and anomaly detection. Traditional …