Liang Yu

Deep Learning and Bayesian inference for Inverse Problems

2023 · arXiv (Cornell University)

Inverse problems arise anywhere we have indirect measurement. As, in general they are ill-posed, to obtain satisfactory solutions for them needs prior knowledge. Classically, different regularization methods and Bayesian inference based methods have been proposed. …

Automated NFR testing in continuous integration environments: a multi-case study of Nordic companies

2023 · Empirical Software Engineering

Abstract Context Non-functional requirements (NFRs) (also referred to as system qualities) are essential for developing high-quality software. Notwithstanding its importance, NFR testing remains challenging, especially in terms of automation. Compared to manual verification, automated testing …

Personalized LoRA for Human-Centered Text Understanding

2024 · arXiv (Cornell University)

Effectively and efficiently adapting a pre-trained language model (PLM) for human-centered text understanding (HCTU) is challenging since user tokens are million-level in most personalized applications and do not have concrete explicit semantics. A standard and …

Retrieval Augmented Instruction Tuning for Open NER with Large Language Models

2024 · arXiv (Cornell University)

The strong capability of large language models (LLMs) has been applied to information extraction (IE) through either retrieval augmented prompting or instruction tuning (IT). However, the best way to incorporate information with LLMs for IE …

Research on Question Generation Based on Free-text

2024

Question generation refers to automatically generating reasonable and relevant questions based on given texts and answers. Past research on question generation has suffered from the following deficiency: in question generation from free texts, the ability …

Measuring the quality of generative AI systems: Mapping metrics to quality characteristics — Snowballing literature review

2025 · Information and Software Technology

Context : Generative Artificial Intelligence (GenAI) and the use of Large Language Models (LLMs) have revolutionized tasks that previously required significant human effort, which has attracted considerable interest from industry stakeholders. This growing interest has …