Chen Yang

Cloud based Real-Time and Low Latency Scientific Event Analysis

2018 · arXiv (Cornell University)

Astronomy is well recognized as big data driven science. As the novel observation infrastructures are developed, the sky survey cycles have been shortened from a few days to a few seconds, causing data processing pressure …

Analyzing host security using D‐S evidence theory and multisource information fusion

2020 · International Journal of Intelligent Systems

Security monitoring and analysis can help users to timely perceive threats faced by the host, thereby protecting and backup data and improving the host's security status. In the research domain of host security analysis, many …

MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation

2021 · arXiv (Cornell University)

Unsupervised domain adaptation (UDA) aims to transfer the knowledge from the labeled source domain to the unlabeled target domain. Existing self-training based UDA approaches assign pseudo labels for target data and treat them as ground …

Enhancing Sequential Recommender with Large Language Models for Joint Video and Comment Recommendation

2024 · arXiv (Cornell University)

Nowadays, reading or writing comments on captivating videos has emerged as a critical part of the viewing experience on online video platforms. However, existing recommender systems primarily focus on users' interaction behaviors with videos, neglecting …

On the Evaluation of Large Language Models in Unit Test Generation

2024 · arXiv (Cornell University)

Unit testing is an essential activity in software development for verifying the correctness of software components. However, manually writing unit tests is challenging and time-consuming. The emergence of Large Language Models (LLMs) offers a new …

Flexpéro: Flexible Expressive Zero-Shot Speech Refinement via In-Context Learning

2025 · IEEE Signal Processing Letters

Controlling speech expressiveness has emerged as a critical research frontier in speech generation, focusing on synthesizing natural, human-like speech that accurately conveys intended psychological and emotional states. While many large-scale models have demonstrated sufficient zero-shot …

An Empirical Study of Pre-trained Transformers for Arabic Information Extraction

2020

Multilingual pre-trained Transformers, such as mBERT However, their performance on Arabic information extraction (IE) tasks is not very well studied. In this paper, we pre-train a customized bilingual BERT, dubbed GigaBERT, that is designed specifically …