Wei Lu
15 papers in the PaperMetrix corpus
Papers by this author
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MRSIM: Mitigating Reducer Skew In MapReduce
2017
MapReduce has emerged as a popular programming model in the field of data-intensive computing. This is due to its simplistic design, which provides ease of use for programmers, and its framework implementations such as Hadoop, …
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Learning Explicit and Implicit Structures for Targeted Sentiment Analysis
2019
Targeted sentiment analysis is the task of jointly predicting target entities and their associated sentiment information. Existing research efforts mostly regard this joint task as a sequence labeling problem, building models that can capture explicit …
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Extraction and Evaluation of Knowledge Entities from Scientific Documents
2021 · Journal of Data and Information Science
Sciendo provides publishing services and solutions to academic and professional organizations and individual authors. We publish journals, books, conference proceedings and a variety of other publications.
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L2NAS
2021
Neural architecture search (NAS) has achieved remarkable results in deep neural network design. Differentiable architecture search converts the search over discrete architectures into a hyperparameter optimization problem which can be solved by gradient descent. However, …
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PersonaMark: Personalized LLM watermarking for model protection and user attribution
2024 · arXiv (Cornell University)
The rapid advancement of customized Large Language Models (LLMs) offers considerable convenience. However, it also intensifies concerns regarding the protection of copyright/confidential information. With the extensive adoption of private LLMs, safeguarding model copyright and ensuring …
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The Sufficient and Necessary Conditions for the Minimum Distance of the BCH Code <i>C</i>(q,q+1,3,h) to Be 3 and 4
2025 · IEEE Transactions on Information Theory
In this paper, the sufficient and necessary conditions for the minimum distance of the BCH code$\mathcal {C}_{(q,q+1,3,h)}$to be 3 and 4 are provided, respectively. Let d be the minimum distance of the BCH code$\mathcal {C}_{(q,q+1,3,h)}$. …
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An Adaptive Federated Fuzzy C-Means Clustering With Nonindependently and Identically Distributed Data
2025 · IEEE Transactions on Systems Man and Cybernetics Systems
Federated Fuzzy C-Means (FCM) has received considerable attention due to the increasing need for privacy-conscious data analysis across diverse domains and sources in many real-world applications. Recent developments in federated FCM, however, are still in …
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Research on paragraph-level functional structure recognition in scientific literature: a data augmentation method based on LLMs and lexical function
2025 · Scientometrics
Abstract The automatic recognition of functional structures within scientific literature enhances fine-grained information retrieval and mitigates issues associated with imbalanced text classification. Although multilevel functional structure research is relatively advanced, achieving high accuracy in overall …
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cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information
2018 · Proceedings of the AAAI Conference on Artificial Intelligence
We propose cw2vec, a novel method for learning Chinese word embeddings. It is based on our observation that exploiting stroke-level information is crucial for improving the learning of Chinese word embeddings. Specifically, we design a …
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Neural Adaptation Layers for Cross-domain Named Entity Recognition
2018
Recent research efforts have shown that neural architectures can be effective in conventional information extraction tasks such as named entity recognition, yielding state-of-the-art results on standard newswire datasets. However, despite significant resources required for training …
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Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning
2019 · Transactions of the Association for Computational Linguistics
We focus on graph-to-sequence learning, which can be framed as transducing graph structures to sequences for text generation. To capture structural information associated with graphs, we investigate the problem of encoding graphs using graph convolutional …
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Attention Guided Graph Convolutional Networks for Relation Extraction
2019
Dependency trees convey rich structural information that is proven useful for extracting relations among entities in text. However, how to effectively make use of relevant information while ignoring irrelevant information from the dependency trees remains …
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Aligning Cross-Lingual Entities with Multi-Aspect Information
2019
Hsiu-Wei Yang, Yanyan Zou, Peng Shi, Wei Lu, Jimmy Lin, Xu Sun. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). …
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Reasoning with Latent Structure Refinement for Document-Level Relation Extraction
2020
Document-level relation extraction requires integrating information within and across multiple sentences of a document and capturing complex interactions between inter-sentence entities. However, effective aggregation of relevant information in the document remains a challenging research question. …
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Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders
2020
Named entity recognition and relation extraction are two important fundamental problems. Joint learning algorithms have been proposed to solve both tasks simultaneously, and many of them cast the joint task as a table-filling problem. However, …