Xiang Chen

An Empirical Study of High-Impact Factors for Machine Learning-Based Vulnerability Detection

2020

Ahstract-Vulnerability detection is an important topic of software engineering. To improve the effectiveness and efficiency of vulnerability detection, many traditional machine learning-based and deep learning-based vulnerability detection methods have been proposed. However, the impact of …

The Method for Extracting New Login Sentiment Words from Chinese Micro-Blog Basedf on Improved Mutual Information

2020 · Computer Systems Science and Engineering

The current method of extracting new login sentiment words not only ignores the diversity of patterns constituted by new multi-character words (the number of words is greater than two), but also disregards the influence of …

Efficient Neural Network Implementation with Quadratic Neuron

2020 · arXiv (Cornell University)

Previous works proved that the combination of the linear neuron network with nonlinear activation functions (e.g. ReLu) can achieve nonlinear function approximation. However, simply widening or deepening the network structure will introduce some training problems. …

Cross-Domain Sentiment Classification with In-Domain Contrastive Learning

2020 · arXiv (Cornell University)

Contrastive learning (CL) has been successful as a powerful representation learning method. In this paper, we propose a contrastive learning framework for cross-domain sentiment classification. We aim to induce domain invariant optimal classifiers rather than …

AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba

2021

Conceptual graphs, which is a particular type of Knowledge Graphs, play an essential role in semantic search. Prior conceptual graph construction approaches typically extract high-frequent, coarse-grained, and time-invariant concepts from formal texts such as Wikipedia. …

WIND: Weighting Instances Differentially for Model-Agnostic Domain Adaptation

2021

Domain Adaptation is a fundamental problem in machine learning and natural language processing. In this paper, we study the domain adaptation problem from the perspective of instance weighting. Conventional instance weighting approaches cannot learn the …

Do we need to pay technical debt in blockchain software systems?

2022 · Connection Science

For blockchain software systems, framework developers may introduce technical debts that application developers are not aware of. Because these technical debts can have a negative impact on software projects, we need to investigate the issue …

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 …

K-Buffers: A Plug-in Method for Enhancing Neural Fields with Multiple Buffers

2024

Neural fields are now the central focus of research in 3D vision and computer graphics. Existing methods mainly focus on various scene representations, such as neural points and 3D Gaussians. However, few works have studied …

LongLaMP: A Benchmark for Personalized Long-form Text Generation

2024 · arXiv (Cornell University)

Long-text generation is seemingly ubiquitous in real-world applications of large language models such as generating an email or writing a review. Despite the fundamental importance and prevalence of long-text generation in many practical applications, existing …

Knowledge Mechanisms in Large Language Models: A Survey and Perspective

2024

Mengru Wang, Yunzhi Yao, Ziwen Xu, Shuofei Qiao, Shumin Deng, Peng Wang, Xiang Chen, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen, Ningyu Zhang. Findings of the Association for Computational Linguistics: EMNLP 2024. …

Document-level Relation Extraction as Semantic Segmentation

2021

Document-level relation extraction aims to extract relations among multiple entity pairs from a document. Previously proposed graph-based or transformer-based models utilize the entities independently, regardless of global information among relational triples. This paper approaches the …

KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction

2022 · Proceedings of the ACM Web Conference 2022

Recently, prompt-tuning has achieved promising results for specific few-shot classification tasks. The core idea of prompt-tuning is to insert text pieces (i.e., templates) into the input and transform a classification task into a masked language …