2023:
Zhan Shi, Guoyin Wang, Ke Bai, Jiwei Li, Xiang Li, Qingjun Cui, Belinda Zeng, Trishul Chilimbi, Xiaodan Zhu. 2023. OssCSE: Overcoming Surface Structure Bias in Contrastive Learning for Unsupervised Sentence Embedding, Proceedings of International Conference on Empirical Methods in Natural Language Processing (EMNLP).
Chu Fei Luo, Rohan V Bhambhoria, Samuel Dahan, Xiaodan Zhu. 2023. Legally Enforceable
Hate Speech Detection for Public Forums, Findings of International Conference on Empirical Methods in Natural Language Processing (EMNLP Findings).
Hui Liu, Qingyu Yin, Zhengyang Wang, Chenwei Zhang, Haoming Jiang, Yifan Gao, Zheng Li, Xian Li, Chao Zhang, Bing Yin, William Yang Wang, Xiaodan Zhu. 2023. Knowledge-Selective Pretraining for Attribute Value Extraction, Findings of International Conference on Empirical Methods in Natural Language Processing (EMNLP Findings).
Xianzhi Li, Samuel Chan, Xiaodan Zhu, Yulong Pei, Zhiqiang Ma, Xiaomo Liu, Sameena Shah. 2023. Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Tasks, Industrial Track of International Conference on Empirical Methods in Natural Language Processing (EMNLP Industrial Track).
Ziou Zheng, Xiaodan Zhu. 2023. NatLogAttack: A Framework for Attacking Natural Language Inference Models with Natural Logic, Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics (ACL).
Rohan Bhambhoria, Xiaodan Zhu, Lei Chen. 2023. A Simple and Effective Framework for Strict Zero-Shot Hierarchical Classification, Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics (ACL).
Jonathan Li, Will Aitken, Rohan Bhambhoria, Xiaodan Zhu. 2023. Prefix Propagation: Parameter-Efficient Tuning for Long Sequences, Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics (ACL).
Chu-Fei Luo, Rohan Bhambhoria, Xiaodan Zhu, Samuel Dahan. 2023. Prototype-Based Interpretability for Legal Citation Prediction, Proceedings of Findings of the 61th Annual Meeting of the Association for Computational Linguistics (Findings of ACL).
Clinton Lau, Xiaodan Zhu, Geoffrey Chan. 2023. Automatic Depression
Severity Assessment with Deep Learning using Parameter-efficient
Tuning, Frontiers in Psychiatry. Volume 14, pages 1160291.
Tianqi Wang, Lei Chen, Xiaodan Zhu, Younghun Lee, Jing Gao. 2023. Weighted Contrastive Learning With False Negative Control to Help Long-tailed Product Classification, Proceedings of Industrial Track of the 61th Annual Meeting of the Association for Computational Linguistics (ACL Industrial Track).
Maede Ashofteh Barabadi, Xiaodan Zhu, Wai Yip Chan, Richard Kinh Do, Amber L. Simpson. 2023. Parameter-Efficient Methods for Metastases Detection from Clinical Notes, Proceedings of the 36th Canadian Conference on Artificial Intelligence. Montreal.
Paul Quinlan, Qingguo Li, Xiaodan Zhu. 2023. Guided Learning of Human Sensor Models with Low-Level Grounding, Proceedings of the 36th Canadian Conference on Artificial Intelligence. Montreal.
2022:
Rohan Bhambhoria, Hui Liu, Samuel Dahan, Xiaodan Zhu. 2022. Interpretable Low-Resource Legal Decision Making, Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI).
Zhan Shi, Yilin Shen, Hongxia Jin, and Xiaodan Zhu. 2022. Improving Zero-Shot Phrase Grounding via Reasoning on External Knowledge and Spatial Relations, Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI).
Yufei Feng, Xiaoyu Yang, Michael Greenspan, Xiaodan Zhu. 2022. Neuro-symbolic Natural Logic with Introspective Revision
for Natural Language Inference, Transactions of the Association for Computational Linguistics (TACL).
Hou Wei Chou, Lei Chen, Xiaodan Zhu. 2022. Developing Prefix-Tuning Models for Hierarchical Text Classification, Proceedings of the Industrial Track of International Conference on Empirical Methods in Natural Language Processing (EMNLP Industrial Track).
Stephen Obadinma, et al. 2022. Bringing the State-of-the-Art to Customers: A Neural Agent Assistant Framework for Customer Service Support, Proceedings of the Industrial Track of International Conference on Empirical Methods in Natural Language Processing (EMNLP Industrial Track).
Jonathan Li, Rohan Bhambhoria, Xiaodan Zhu. 2022. Parameter-Efficient Legal Domain Adaptation., Proceedings of the EMNLP Workshop on Natural Legal Language Processing (NLLP) .
Xianzhi Li, Will Aitken, Xiaodan Zhu, Stephen W. Thomas. 2022. Learning Better Intent Representations for Financial Open Intent Classification, Proceedings of the EMNLP Workshop on Financial Technology and Natural Language Processing (FinNLP).
Sudhandar Balakrishnan, Yihao Fang, Xiaodan Zhu. 2022. . Exploring Robustness of Prefix Tuning in Noisy Data: A Case Study in Financial Sentiment Analysis, Proceedings of the EMNLP Workshop on Financial Technology and Natural Language Processing (FinNLP).
Chu-Fei Luo, Rohan Bhambhoria, Samuel Dahan and Xiaodan Zhu. 2022. Evaluating Explanation Correctness in Legal Decision Making, Proceedings of the 35th Canadian Conference on Artificial Intelligence .
2021:
Hui Liu, Zhan Shi, Xiaodan Zhu. 2021. Unsupervised Conversation Disentanglement through Co-Training, Proceedings of International Conference on Empirical Methods in Natural Language Processing (EMNLP).
Weinan He, Canming Huang, Yongmei Liu, Xiaodan Zhu. 2021. WinoLogic: A Zero-Shot Logic-based Diagnostic Dataset for Winograd Schema Challenge, Proceedings of International Conference on Empirical Methods in Natural Language Processing (EMNLP).
Stephen Obadinma, Hongyu Guo, Xiaodan Zhu. 2021. Class-wise Calibration: A Case Study on COVID-19 Hate Language. The 34th Canadian Conference on Artificial Intelligence. (Best Paper Award).
Samuel Dahan, Rohan Bhambhoria, Simon Townsend, Xiaodan Zhu. 2021. Analytics and EU Courts: The Case of Trademark Disputes. Book chapter. In: Changing European Union: A Critical View on the Role of Law and the Courts. Edited by: Tamara Capetais, Iris Goldner Lang, and Tamara Perisinis.
Xiaoyu Yang, Xiaodan Zhu. 2021 Exploring Decomposition for Table-based Inference and Fact Verification, In Findings of the International Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP). Short paper.
Hui Liu, Danqi Zhang, Bing Yin, Xiaodan Zhu. 2021. Improving Pretrained Models for Zero-shot Multi-label Text Classification through Reinforced Label Hierarchy Reasoning, Proceedings of 20th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). Online.
Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu. 2021. Investigating the State-of-the-Art Performance and Explainability of Legal Judgment Prediction. The 34th Canadian Conference on Artificial Intelligence.
Jia-Chen Gu, Tianda Li, Zhen-Hua Ling, Quan Liu, Ziming Su, Yu-Ping Ruan, Xiaodan Zhu. 2021. Deep Contextualized Utterance Representations for Response Selection and Dialogue Analysis. IEEE/ACM Transactions on Audio, Speech, and Language Processing (IEEE/ACM TASLP).
Zhan Shi, Hui Liu, Xiaodan Zhu. 2021. Enhancing Descriptive Image Captioning with Natural Language Inference. The 59th Annual Meeting of the Association for Computational Linguistics (ACL) Short paper.
Binyuan Hui, Ruiying Geng, Qiyu Ren, Binhua Li, Yongbin Li, Jian Sun, Fei Huang, Luo Si, Pengfei Zhu, Xiaodan Zhu. 2021. Dynamic Hybrid Relation Exploration Network for Cross-Domain Context-Dependent Semantic Parsing., Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI).
2020:
Zhan Shi, Xu Zhou, Xipeng Qiu, and Xiaodan Zhu. 2020. Improving Image Captioning with Better Use of Caption The 59th Annual Meeting of the Association for Computational Linguistics (ACL). Seattle, USA.
Yongfei Liu, Bo Wan, Xiaodan Zhu, and Xuming He. 2020. Learning Cross-modal Context Graph Networks for Visual Grounding, Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI). New York City, NY, USA.
Yu-Ping Ruan, Zhen-Hua Ling, Xiaodan Zhu, Quan Liu, and Jia-Chen Gu. 2020. Generating Diverse Conversational Responses by Creating and Ranking Multiple Candidates, Computer Speech & Language, Volume 62, 2020.
Ruiying Ge, Binghua Li, Yongbin Li, Jian Sun and Xiaodan Zhu. 2020. Dynamic Memory Induction Networks for Few-Shot Text Classification, The 59th Annual Meeting of the Association for Computational Linguistics (ACL). Short paper. Seattle, USA.
Yinpei Dai, Hangyu Li, Chengguang Tang, Yongbin Li, Jian Sun, and Xiaodan Zhu. 2020. Learning Low-Resource End-To-End Goal-Oriented Dialog for Fast and Reliable System Deployment. The 59th Annual Meeting of the Association for Computational Linguistics (ACL). Short paper. Seattle, USA.
Xiaoyan Li, Iluju Kiringa, Tet Yeap, Xiaodan Zhu and Yifeng Li. 2020. Anomaly Detection Based on Unsupervised Disentangled Representation Learning in Combination with Manifold Learning, International Joint Conference on Neural Networks (IJCNN). Glasgow, UK.
Karly Kudrinko, Emile Flavin, Xiaodan Zhu, Qingguo Li. 2020. Wearable Sensor-Based Sign Language Recognition: A Comprehensive Review, IEEE Reviews in Biomedical Engineering. (Impact factor: 6.18)
Xiaoyu Yang, Stephen Obadinma, Huasha Zhao, Qiong Zhang, Stan Matwin, and Xiaodan Zhu. 2020. SemEval-2020 Task 5: Counterfactual Recognition. The 14th International Workshop on Semantic Evaluation (SemEval-2020). Barcelona, Spain.
* We organized this shared task in SemEval-2020. The data, leaderboard, and performances of the participating teams are available at [link]. We invite you to use this dataset for further research and post-competition evaluation. [paper] [proposal]
Cunxiang Wang, Shuailong Liang, Yili Jin, Yilong Wang, Xiaodan Zhu, and Yue Zhang. 2020. SemEval-2020 Task 4: Commonsense Validation and Explanation. The 14th International Workshop on Semantic Evaluation (SemEval-2020). Barcelona, Spain.
* For this shared task, the data, leaderboard, and performances of the participating teams are available at [link]. We invite you to use this dataset for further research and post-competition evaluation.
Jia-Chen Gu, Tianda Li, Quan Liu, Zhen-Hua Ling, Zhiming Su, Si Wei, Xiaodan Zhu. 2020. Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots. The 29th ACM International Conference on Information and Knowledge Management. (CIKM). Short paper. Galway, Ireland.
Xiaoyan Li, Iluju Kiringa, Tet Yeap, Xiaodan Zhu and Yifeng Li. 2020. Exploring Deep Anomaly Detection Methods Based on Capsule Net. The 33rd Canadian Conference on Artificial Intelligence. Ottawa, Canada.
Jia-Chen Gu, Tianda Li, Quan Liu, Xiaodan Zhu, Zhen-Hua Ling, Yu-Ping Ruan. 2020. Pre-Trained and Attention-Based Neural Networks for Building Noetic Task-Oriented Dialogue Systems, AAAI Workshop: The Eighth Dialog System Technology Challenge (DSTC-8). New York City, NY, USA.
Iabal Singh, Xiaodan Zhu, and Michael Greenspan. 2020. Multi-modal Fusion with Observation Points for Skeleton Action Recognition, The 27th International Conference on Image Processing (ICIP). Dubai, UAE.
2019:
Samuel R. Bowman and Xiaodan Zhu. 2019. Deep Learning for Natural Language Inference, NAACL-2019 tutorial. [Slides][Description]
Yifeng Li and Xiaodan Zhu. 2019.Capsule Generative Models. International Conference on Artificial Neural Networks (ICANN), Munich, Germany.
Jia-Chen Gu, Zhen-Hua Ling, Xiaodan Zhu and Quan Liu. 2019. Dually Interactive Matching Network for Personalized Response Selection in Retrieval-Based Chatbots. International Conference on Empirical Methods in Natural Language Processing (EMNLP), Hong Kong, China.
Ruiying Geng, Binhua Li, Yongbin Li, Xiaodan Zhu, Ping Jian and Jian Sun. 2019. Induction Networks for Few-Shot Text Classification. International Conference on Empirical Methods in Natural Language Processing (EMNLP), Hong Kong, China.
Parinaz Sobhani, Diana Inkpen, and Xiaodan Zhu. 2019. Exploring Deep Neural Networks for Multi-Target Stance Detection. Computational Intelligence, 35(1), 82-97
Xiaoyu Yang, Xiaodan Zhu, Huasha Zhao, Qiong Zhang, and Yufei Feng. 2019. Enhancing Unsupervised Pretraining with External Knowledge for Natural Language Inference. The 32nd Canadian Conference on Artificial Intelligence. Kingston, Canada.
Xiaoyan Li, Iluju Kiringa, Tet Yeap, Xiaodan Zhu, and Yifeng Li. 2019. Exploring Deep Anomaly Detection Methods Based on Capsule Network. ICML 2019 Workshop on Uncertainty & Robustness in Deep Learning, Long Beach, USA.
2018:
Yufei Feng, Xiaodan Zhu, Yifeng Li, Yuping Ruan, and Michael Greenspan. 2018. Learning Capsule Networks with Images and Text. The NIPS Workshop on Visually Grounded Interaction and Language (ViGIL).
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Diana Inkpen, and Si Wei. 2018. Neural Natural Language Inference Models Enhanced with External Knowledge. The 56th Annual Meeting of the Association for Computational Linguistics (ACL).
(*Achieves state-of-the-art results on Stanford Natural Language Inference Dataset.)
Yifeng Li and Xiaodan Zhu. 2018. Exponential Family Restricted Boltzmann Machines and Annealed Importance Sampling. .
Qian Chen, Zhen-Hua Ling, and Xiaodan Zhu. 2018. Enhancing Sentence Embedding with Generalized Pooling. The 27th International Conference on Computational Linguistics (COLING). Santa Fe, New Mexica, USA.
Yifeng Li and Xiaodan Zhu. 2018. Capsule Restricted Boltzmann Machine
. The NIPS Workshop on Bayesian Deep Learning.
Yifeng Li and Xiaodan Zhu. 2018. Exploring Helmholtz Machine and Deep Belief Net in the Exponential Family Perspective. ICML Workshop on Theoretical Foundations and Applications of Deep Generative Models.
Vo Duy Tin, Yue Zhang, and Xiaodan Zhu. 2018. Shallow Network with Rich Features for Text Classification. The 19th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing).
2017:
Xiaodan Zhu and Edward Grefenstette. 2017. Deep Learning for Semantic Composition, ACL-2017 tutorial. [Slides][Description]
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Si Wei, Hui Jiang, and Diana Inkpen. 2017. Enhanced LSTM for Natural Language Inference, Proceedings of The 55th annual meeting of the Association for Computational Linguistics (ACL). Vancouver, Canada.
*achieves state-of-the-art results on Stanford Natural Language Inference benchmark.
Qian visited me and Prof. Diana Inkpen working on deep learning for sentence representation and natural language inference.
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Si Wei, Hui Jiang, and Diana Inkpen. 2017. Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference, Proceedings of EMNLP-2017 Workshop on Evaluating Vector Space Representations for NLP(RepEval). Copenhagen, Denmark.
*Our model (alpha) is among the top in RepEval-17 Shared Task [link]. The neural networks attempt to encode the meaning of sentences into fixed-length vectors; the effectiveness of the models is evaluated with Natural Langauge Inference.
Quan Liu, Hui Jiang, Andrew Evdokimov, Zhen-Hua Ling, Xiaodan Zhu, Si Wei, and Yu Hu. 2017. Cause-Effect Knowledge Acquisition and Neural Association Models for Solving a Set of Winograd Schema Problems, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI). Melbourne, Australia.
Parinaz Sobhani, Diana Inkpen, and Xiaodan Zhu. 2017. A Dataset for Multi-Target Stance Detection, Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics, (EACL), short paper. Valencia, Spain.
Quan Liu, Hui Jiang, Zhen-Hua Ling, Xiaodan Zhu, Si Wei, and Yu Hu. 2017. Combining Context and
Commonsense Knowledge through Neural Networks for Solving Winograd Schema Problems, AAAI
Spring Symposium. Stanford University, USA.
2016:
Xiaodan Zhu, Parinaz Sobhani, and Hongyu Guo. 2016. DAG-Structured Long Short-Term Memory for Semantic Compositionality, Proceedings of the Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL). San Diego, USA.
Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, and Hui Jiang. Distraction-Based Neural Networks for Document Summarization. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) , New York, USA.
Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, and Hui Jiang. 2016. Enhancing and Combining Sequential and Tree LSTM for Natural Language Inference, arXiv:1609.06038.
Saif M Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016. Semeval-2016 task 6: Detecting stance in tweets. Proceedings of the International Workshop on Semantic Evaluation (SemEval).
Yunli Wang, Yong Jing, Xiaodan Zhu, and Cyril Goutte. 2016. Extracting Discriminative Keyphrases with Learned Semantic Hierarchies, International Conference on Computational Linguistics (COLING). Osaka, Japan.
Preslav Nakov, Sara Rosenthal, Svetlana Kiritchenko, Saif Mohammad, Zornitsa Kozareva, Alan Ritter, Veselin Stoyanov, and Xiaodan Zhu. 2016. Developing a successful SemEval task in sentiment analysis of Twitter and other social media texts. Language Resources and Evaluation (LREC). 50(1), 35-65.
Saif M Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016. A dataset for detecting stance in tweets. Proceedings of 10th edition of the the Language Resources and Evaluation. Portorož, Slovenia.
2015:
We proposed Tree LSTM:
Xiaodan Zhu, Parinaz Sobhani, Hongyu Guo. 2015. Long Short-Term Memory over Tree Structures, Proceedings of International Conference on Machine Learning (ICML). Lille, France. (An earlier arXiv version and the more recent ICML version with updated results are both available below).
Xiaodan Zhu, Hongyu Guo, and Parinaz Sobhani. Neural Networks for Integrating Compositional and Non-compositional Sentiment in Sentiment Composition, Proceedings of Joint conference on Lexical and Computational Semantics (*SEM). Denver, Colorado (Best Paper Award).
Hongyu Guo, Xiaodan Zhu, and Renqiang Min (co-first authors). A Deep Learning Model for Structured Outputs with High-order Interaction, In Proceedings of NIPS Workshop on Representation and Learning Methods for Complex Outputs. Montreal, Canada.
Zhigang Chen, Wei Lin, Qian Chen, Si Wei, Hui Jiang, and Xiaodan Zhu. 2015. Revisiting Word Embedding for Contrasting Meaning. Proceedings of the 52th Annual Meeting of the Association for Computational Linguistics (ACL), Beijing, China.
Xiaodan Zhu, Peter Turney, Daniel Lemire, and Andre Vellino. 2014. Measuring academic influence: Not all citations are equal. Journal of the Association for Information Science and Technology (JASIST), 66(2), 408--427, 2015.
2014:
Xiaodan Zhu, Hongyu Guo,Svetlana Kiritchenko, Saif Mohammad. 2014.
An Empirical Study on the Effect of Negation Words on Sentiment. In Proceedings of the 52th Annual Meeting of the Association for Computational Linguistics (ACL). Baltimore, USA.
Saif Mohammad, Xiaodan Zhu, Svetlana Kiritchenko, and Joel Martin. Sentiment, Emotion, Purpose, and Style in Electoral Tweets. Journal of Information Processing; Management (IPM). 51(4), pages 480-499, 2015.
Svetlana Kiritchenko, Xiaodan Zhu, Saif Mohammad. 2014. Sentiment Analysis of Short Informal Texts. Journal of Artificial Intelligence Research (JAIR). volume 50, pages 723-762, August 2014
Xiaodan Zhu, Svetlana Kiritchenko, and Saif Mohammad. 2014. NRC-Canada-2014: Recent Improvements in the Sentiment Analysis of Tweets. In Proceedings of the International Workshop on Semantic Evaluation. Dublin, Ireland.
* Describing our top-performing models in the Semeval-2014 International Competition on Sentiment Analysis in Twitter; our models ranked first in five of the ten subtask-domain combinations among about 40 participating teams from the world.
Boxing Chen and Xiaodan Zhu. 2014. Bilingual Sentiment Consistency for Statistical Machine Translation. In Proceedings of Conference of the European Chapter of the Association for Computational Linguistics (EACL). Gothenburg, Sweden.
Saif M. Mohammad, Xiaodan Zhu, and Joel Martin. 2014. Semantic Role Labeling of Emotions in Tweets. In Proceedings of ACL Workshop on Computational Approaches to Subjectivity, Sentiment Social Media Analysis (WASSA), Baltimore, USA.
Svetlana Kiritchenko, Xiaodan Zhu, and Saif Mohammad. 2014. NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews. In Proceedings of the International Workshop on Semantic Evaluation. Dublin, Ireland.
* Describing our top-performing models in Semeval-2014 Task-4: Aspect Based
Sentiment Analysis.
2013:
Saif M. Mohammad, Svetlana Kiritchenko, and Xiaodan Zhu (Co-first authors). 2013. NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets. In Proceedings of the International Workshop on Semantic Evaluation, Atlanta, USA.
Colin Cherry, Xiaodan Zhu, Joel Martin, and Berry De Bruijn. A la Recherche du Temps Perdu - Extracting Temporal Relations from Medical Text in the 2012 i2b2 NLP Challenge. Journal of the American Medical Informatics Association (JAMIA). 20(5): 843-848 (2013)
Xiaodan Zhu, Colin Cherry, Svetlana Kiritchenko, Joel Martin, and Berry de Bruijn. Detecting Concept Relations in Clinical Text: Insights from A State-of-The-Art Model. Journal of Biomedical Informatics (JBI) 46(2): 275-285 (2013).
2012:
Xiaodan Zhu. 2012. Spotting keywords and sensing topic changes in speech. In Proceedings of Computational Intelligence for Security and Defence Applications, Ottawa, Canada.
Anthony McCallum, Cosmin Munteanu, Gerald Penn, Xiaodan Zhu. 2012. Ecological Validity and the Evaluation of Speech Summarization Quality. In Proceedings of NAACL Workshop on Evaluation Metrics and System Comparison for Automatic Summarization, Montreal, Canada.
2011:
Berry de Bruijn, Colin Cherry, Svetlana Kiritchenko, Joel Martin, and Xiaodan Zhu. Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010. Journal of the American Medical Informatics Association (JAMIA), May 2011.
*Our approaches were ranked at two first places and one second place, among more than 40 international teams in i2b2-2010 medical information extraction challenge. I led NRC's effort on the relation extraction challenge, one of the three official challenges.
Xiaodan Zhu, Colin Cherry, and Gerald Penn. 2013. A Graph-partitioning Framework for Aligning Hierarchical Topic Structures to Presentations. ACM/IEEE Transaction on Audio, Speech, and Language Processing (TASLP) 21(5): 1102-1112.
Xiaodan Zhu. 2011. A Normalized-Cut Alignment Model for Mapping Hierarchical Semantic Structures onto Spoken Documents. In Proceedings of Conference on Computational Natural Language Learning (CONLL), Portland, Oregon, USA
Xiaodan Zhu, Colin Cherry and Gerald Penn. 2011. Indexing Spoken Documents with Hierarchical Semantic Structures: Semantic Tree-to-string Alignment Models. In Proceedings of International Joint Conference on Natural Language Processing (IJCNLP), Chiangmai, Thailand.
2010:
Xiaodan Zhu, Colin Cherry, and Gerald Penn. 2010. Imposing Hierarchical Browsing Structures onto Spoken Documents. In Proceedings of International Conference on Computational Linguistics (COLING), Beijing, China.
2009:
Xiaodan Zhu, Gerald Penn and Frank Rudzicz. 2009. Summarizing multiple spoken documents: finding evidence from untranscribed audio. In Proceedings of the 47th Annual Meeting of Association for Computational Linguistics(ACL), Singapore.
Cosmin Munteanu, Gerald Penn, and Xiaodan Zhu. 2009. Improving Automatic Speech Recognition for Lectures through Transformation-based Rules Learned from Minimal Data. In Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics(ACL), Singapore.
2008:
Gerald Penn and Xiaodan Zhu. A critical reassessment of evaluation baselines for speech summarization of spontaneous conversations. In Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics (ACL), Columbus, USA.
Xiaodan Zhu, Xuming He, Cosmin Munteanu, and Gerald Penn. 2008. Using latent Dirichlet allocation to incorporate domain knowledge for topic transition detection. In Proceedings of the International Conference on Spoken Language Processing (Interspeech), Brisbane, Australia.
Xiaodan Zhu, Siavash Kazemian, and Gerald Penn. 2008. Identifying salient utterances from Web spoken documents using descriptive hypertext. In Proceedings of IEEE Workshop on Spoken Language Technology (SLT), Goa, India.
Bowen Zhou, Xiaodan Zhu, Bing Xiang, and Yuqing Gao. 2008. Prior derivation models for formally syntax-based translation using linguistically syntactic parsing and tree kernels. In Proceedings of ACL Workshop on Syntax and Structure in Statistical Translation, Columbus, USA.
2007 and earlier:
Yun Niu, Xiaodan Zhu, and Graeme Hirst. 2006. Using Outcome Polarity in Sentence Extraction for
Medical Question-Answering. In Proceedings of the Annual Symposium of the American Medical Informatics Association (AMIA), Washington, D.C., USA.
Xiaodan Zhu and Gerald Penn. 2006. Summarization of spontaneous conversations. In Proceedings of the International Conference on Spoken Language Processing (Interspeech), Pittsburgh, Pennsylvania, USA.
Xiaodan Zhu and Gerald Penn. 2006. Comparing the roles of textual, acoustic and spoken-language features on spontaneous-conversation summarization. In Proceedings of the Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL), New York, USA.
Xiaodan Zhu and Gerald Penn. 2005. Evaluation of sentence selection for speech summarization. In Proceedings of RANLP Workshop Crossing Barriers in Text Summarization Research, Borovets, Bulgaria.
Yun Niu, Xiaodan Zhu, Jianhua Li, and Graeme Hirst. 2005. Analysis of polarity information in medical text. In Proceedings of the Annual Symposium of the American Medical Informatics Association (AMIA), Washington, D.C.
Xiaodan Zhu, Mu Li, Jianfeng Gao, and Chang-Ning Huang. 2003. Single character Chinese Named Entity Recognition, In Proceedings of ACL SIGHAN Workshop on Chinese Language Processing, Sapporo, Japan.
Kam-Fai Wong, Wenjie Li, Chunfa Yuan, and Xiaodan Zhu. 2002. Temporal representation and classification in Chinese. International Journal of Computer Processing of Oriental Languages. 15(2): 211-230.
Xiaodan Zhu, Qian Diao, and Joe F. Zhou. 2001. A Two-Character Hash Function for Chinese Word Indexing. In Proceedings of the 6th National Joint Conference of Computational Linguistics of China, Taiyuan, China.
Xiaodan Zhu and Chunfa Yuan. 2000. An Algorithm for Situation Classification of Chinese Verbs, In Proceedings of ACL Workshop on Chinese Language Processing, Hong Kong, China.
Xiaodan Zhu. 2000. Information Extraction from Financial News. Masters Thesis, Tsinghua University, Beijing, China.
Wei Xu, Chunfa Yuan, Changning Huang, and Xiaodan Zhu. A Study on the Combinatorial Regulation of Chinese Semantic Classes, Communication of COLIPS.