2 citations · 5 across the 13 of their papers we have counts for
14 papers
Logi-PAR: Logic-Infused Patient Activity Recognition via Differentiable Rule
Muhammad Zarar, MingZheng Zhang, Xiaowang Zhang +3
Patient Activity Recognition (PAR) in clinical settings uses activity data to improve safety and quality of care. Although significant progress has been made, current models mainly…
Domain-constrained Synthesis of Inconsistent Key Aspects in Textual Vulnerability Descriptions
Linyi Han, Shidong Pan, Zhenchang Xing +5
Textual Vulnerability Descriptions (TVDs) are crucial for security analysts to understand and address software vulnerabilities. However, the key aspect inconsistencies in TVDs from…
Think Like an Engineer: A Neuro-Symbolic Collaboration Agent for Generative Software Requirements Elicitation and Self-Review
Sai Zhang, Zhenchang Xing, Jieshan Chen +5
The vision of End-User Software Engineering (EUSE) is to empower non-professional users with full control over the software development lifecycle. It aims to enable users to drive…
Human-Like Code Quality Evaluation through LLM-based Recursive Semantic Comprehension
Fangzhou Xu, Sai Zhang, Zhenchang Xing +3
Code quality evaluation involves scoring generated code quality based on a reference code for a specific problem statement. Currently, there are two main forms of evaluating code q…
A test-free semantic mistakes localization framework in Neural Code Translation
Lei Chen, Sai Zhang, Fangzhou Xu +4
In the task of code translation, neural network-based models have been shown to frequently produce semantically erroneous code that deviates from the original logic of the source c…
Differentiating Choices via Commonality for Multiple-Choice Question Answering
Wenqing Deng, Zhe Wang, Kewen Wang +3
Multiple-choice question answering (MCQA) becomes particularly challenging when all choices are relevant to the question and are semantically similar. Yet this setting of MCQA can…
Empowering Agile-Based Generative Software Development through Human-AI Teamwork
Sai Zhang, Zhenchang Xing, Ronghui Guo +6
In software development, the raw requirements proposed by users are frequently incomplete, which impedes the complete implementation of application functionalities. With the emerge…
SememeLM: A Sememe Knowledge Enhanced Method for Long-tail Relation Representation
Shuyi Li, Shaojuan Wu, Xiaowang Zhang +1
Recognizing relations between two words is a fundamental task with the broad applications. Different from extracting relations from text, it is difficult to identify relations amon…
BiSup: Bidirectional Quantization Error Suppression for Large Language Models
Minghui Zou, Ronghui Guo, Sai Zhang +2
As the size and context length of Large Language Models (LLMs) grow, weight-activation quantization has emerged as a crucial technique for efficient deployment of LLMs. Compared to…
Relative Counterfactual Contrastive Learning for Mitigating Pretrained Stance Bias in Stance Detection
Jiarui Zhang, Shaojuan Wu, Xiaowang Zhang +1
Stance detection classifies stance relations (namely, Favor, Against, or Neither) between comments and targets. Pretrained language models (PLMs) are widely used to mine the stance…
Do Chase Your Tail! Missing Key Aspects Augmentation in Textual Vulnerability Descriptions of Long-tail Software through Feature Inference
Linyi Han, Shidong Pan, Zhenchang Xing +4
Augmenting missing key aspects in Textual Vulnerability Descriptions (TVDs) is crucial for effective vulnerability analysis. For instance, in TVDs, key aspects include Attack Vecto…
Attribute Simulation for Item Embedding Enhancement in Multi-interest Recommendation
Yaokun Liu, Xiaowang Zhang, Minghui Zou +1
Although multi-interest recommenders have achieved significant progress in the matching stage, our research reveals that existing models tend to exhibit an under-clustered item emb…
Function-words Enhanced Attention Networks for Few-Shot Inverse Relation Classification
Chunliu Dou, Shaojuan Wu, Xiaowang Zhang +2
The relation classification is to identify semantic relations between two entities in a given text. While existing models perform well for classifying inverse relations with large…
Learning by Erasing: Conditional Entropy based Transferable Out-Of-Distribution Detection
Meng Xing, Zhiyong Feng, Yong Su +1
Out-of-distribution (OOD) detection is essential to handle the distribution shifts between training and test scenarios. For a new in-distribution (ID) dataset, existing methods req…