Xu Han
22 ورقة في مجموعة PaperMetrix
أوراق هذا المؤلف
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Software Theater—Teaching Demo-Oriented Prototyping
2018 · ACM Transactions on Computing Education
Modern capstone courses use agile methods to deliver and demonstrate software early in the project. However, a simple demonstration of functional and static aspects does not provide real-world software usage context, although this is integral …
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Compressing Knowledge Graph Embedding with Relational Graph Auto-encoder
2020
Knowledge graphs (KGs) are extremely useful resources for varieties of applications. However, with the large and steadily growing sizes of modern KGs, knowledge graph embeddings (KGE), which represent entities and relations in KGs into 32-bit …
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A Comparative Study on the current situation of Cultural teaching in South Korea and China Language Teaching
2020 · Chunwon Research journal
한·중 양국 간의 교류가 활발해지면서 사람들의 언어와 문화에 대한 이해는 더욱 불가결해졌다. 본문은 주로 외국인 대상으로 한 한국어교육과 중국어교육 중에 문화교육의 공통점과 차이점을 비교하기로 한다. 연구목적은 양국 언어교육 중에 나타난 문화교육 유형, 교육 내용과 교육 …
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Denoising Relation Extraction from Document-level Distant Supervision
2020
Distant supervision (DS) has been widely used to generate auto-labeled data for sentencelevel relation extraction (RE), which improves RE performance. However, the existing success of DS cannot be directly transferred to the more challenging document-level …
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Learning from Context or Names? An Empirical Study on Neural Relation Extraction
2020
Neural models have achieved remarkable success on relation extraction (RE) benchmarks. However, there is no clear understanding which type of information affects existing RE models to make decisions and how to further improve the performance …
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MAVEN: A Massive General Domain Event Detection Dataset
2020
Xiaozhi Wang, Ziqi Wang, Xu Han, Wangyi Jiang, Rong Han, Zhiyuan Liu, Juanzi Li, Peng Li, Yankai Lin, Jie Zhou. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2020.
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Sampling-based Fast Gradient Rescaling Method for Highly Transferable Adversarial Attacks
2022 · arXiv (Cornell University)
Deep neural networks have shown to be very vulnerable to adversarial examples crafted by adding human-imperceptible perturbations to benign inputs. After achieving impressive attack success rates in the white-box setting, more focus is shifted to …
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MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction
2022 · arXiv (Cornell University)
The diverse relationships among real-world events, including coreference, temporal, causal, and subevent relations, are fundamental to understanding natural languages. However, two drawbacks of existing datasets limit event relation extraction (ERE) tasks: (1) Small scale. Due …
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Plug-and-Play Knowledge Injection for Pre-trained Language Models
2023 · arXiv (Cornell University)
Injecting external knowledge can improve the performance of pre-trained language models (PLMs) on various downstream NLP tasks. However, massive retraining is required to deploy new knowledge injection methods or knowledge bases for downstream tasks. In …
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Democratizing Chatbot Debugging: A Computational Framework for Evaluating and Explaining Inappropriate Chatbot Responses
2023
Evaluating and understanding the inappropriateness of chatbot behaviors can be challenging, particularly for chatbot designers without technical backgrounds. To democratize the debugging process of chatbot misbehaviors for non-technical designers, we propose a framework that leverages …
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Exploring Mode Connectivity for Pre-trained Language Models
2022
Recent years have witnessed the prevalent application of pre-trained language models (PLMs) in NLP. From the perspective of parameter space, PLMs provide generic initialization, starting from which high-performance minima could be found. Although plenty of …
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Quantum hypothesis testing via robust quantum control
2023 · arXiv (Cornell University)
Quantum hypothesis testing plays a pivotal role in quantum technologies, making decisions or drawing conclusions about quantum systems based on observed data. Recently, quantum control techniques have been successfully applied to quantum hypothesis testing, enabling …
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Interpretability in Sentiment Analysis: A Self-Supervised Approach to Sentiment Cue Extraction
2024 · Applied Sciences
In this paper, we present a novel self-supervised framework for Sentiment Cue Extraction (SCE) aimed at enhancing the interpretability of text sentiment analysis models. Our approach leverages self-supervised learning to identify and highlight key textual …
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Cognitive Mirroring for DocRE: A Self-Supervised Iterative Reflection Framework with Triplet-Centric Explicit and Implicit Feedback
2025
Large language models (LLMs) have advanced document-level relation extraction (DocRE), but DocRE is more complex than sentencelevel relation extraction (SentRE), facing challenges like diverse relation types, coreference resolution and long-distance dependencies.Traditional pipeline methods, which detect …
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Neural Knowledge Acquisition via Mutual Attention Between Knowledge Graph and Text
2018 · Proceedings of the AAAI Conference on Artificial Intelligence
We propose a general joint representation learning framework for knowledge acquisition (KA) on two tasks, knowledge graph completion (KGC) and relation extraction (RE) from text. In this framework, we learn representations of knowledge graphs (KGs) …
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GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification
2019
Fact verification (FV) is a challenging task which requires to retrieve relevant evidence from plain text and use the evidence to verify given claims. Many claims require to simultaneously integrate and reason over several pieces …
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DocRED: A Large-Scale Document-Level Relation Extraction Dataset
2019
Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou, Maosong Sun. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019.
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ERNIE: Enhanced Language Representation with Informative Entities
2019
Neural language representation models such as BERT pre-trained on large-scale corpora can well capture rich semantic patterns from plain text, and be fine-tuned to consistently improve the performance of various NLP tasks. However, the existing …
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FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation
2018
We present a Few-Shot Relation Classification Dataset (FewRel), consisting of 70, 000 sentences on 100 relations derived from Wikipedia and annotated by crowdworkers. The relation of each sentence is first recognized by distant supervision methods, …
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OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction
2019
Xu Han, Tianyu Gao, Yuan Yao, Deming Ye, Zhiyuan Liu, Maosong 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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FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
2019
Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language …
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PTR: Prompt Tuning with Rules for Text Classification
2022 · AI Open
Recently, prompt tuning has been widely applied to stimulate the rich knowledge in pre-trained language models (PLMs) to serve NLP tasks. Although prompt tuning has achieved promising results on some few-class classification tasks, such as …