Guang Yang

SOTitle: A Transformer-based Post Title Generation Approach for Stack Overflow

2022 · arXiv (Cornell University)

On Stack Overflow, developers can not only browse question posts to solve their programming problems but also gain expertise from the question posts to help improve their programming skills. Therefore, improving the quality of question …

Data Harmonisation for Information Fusion in Digital Healthcare: A State-of-the-Art Systematic Review, Meta-Analysis and Future Research Directions

2022 · arXiv (Cornell University)

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and …

Prompt learning for metonymy resolution: Enhancing performance with internal prior knowledge of pre-trained language models

2023 · Knowledge-Based Systems

Linguistic metonymy is a common type of figurative language in natural language processing (NLP), where a concept is represented by a closely associated word or phrase, for example “business executives suits”. As a result, metonymy …

Assessing the Efficacy of Invisible Watermarks in AI-Generated Medical Images

2024 · arXiv (Cornell University)

AI-generated medical images are gaining growing popularity due to their potential to address the data scarcity challenge in the real world. However, the issue of accurate identification of these synthetic images, particularly when they exhibit …

Dynamic Multimodal Information Bottleneck for Multimodality Classification

2024

Effectively leveraging multimodal data such as various images, laboratory tests and clinical information is becoming increasingly attractive in a variety of AI-based medical diagnosis and prognosis tasks. Most existing multi-modal techniques only focus on enhancing …

Beyond Logarithmic Bounds: Querying in Constant Expected Time with Learned Indexes

2024 · arXiv (Cornell University)

Learned indexes leverage machine learning models to accelerate query answering in databases, showing impressive practical performance. However, theoretical understanding of these methods remains incomplete. Existing research suggests that learned indexes have superior asymptotic complexity compared …

PQPU: A 4.4-<i>μ</i>J/Op 69.4-kOPS Agile Post-Quantum Crypto-Processor Across Multiple Mathematical Problems

2024 · IEEE Journal of Solid-State Circuits

Post-quantum cryptography (PQC) is currently being standardized to replace the existing public-key cryptography for data security in the era of quantum computing. PQC algorithms exhibit considerable diversity in their underlying mathematical problems, storage requirements, and …

Parameter-efficient fine-tuning of large-scale pre-trained language models

2023 · Nature Machine Intelligence

Abstract With the prevalence of pre-trained language models (PLMs) and the pre-training–fine-tuning paradigm, it has been continuously shown that larger models tend to yield better performance. However, as PLMs scale up, fine-tuning and storing all …