Publications (selected)

2023

§  PESCO: Prompt-enhanced Self Contrastive Learning for Zero-shot Text Classification. Yau-Shian Wang, Ta-Chung Chi, Ruohong Zhang, Yiming Yang.  ACL 2023: 14897-14911

§  PAL: Program-aided Language Models. Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, Graham Neubig. ICML 2023: 10764-10799

§  A Neural PDE Solver with Temporal Stencil Modeling. Zhiqing Sun, Yiming Yang, Shinjae Yoo. ICML 2023: 33135-33155

§  Retrieval-Enhanced Generative Model for Large-Scale Knowledge Graph Completion. Donghan Yu, Yiming Yang. SIGIR 2023: 2334-2338

§  Learning Performance-Improving Code Edits. Aman Madaan, Alexander Shypula, Uri Alon, Milad Hashemi, Parthasarathy Ranganathan, Yiming Yang, Graham Neubig, Amir Yazdanbakhsh. Deep Learning for Code Workshop at ICLR 2023.

§  Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller.  (Under Review)

§  DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization. Zhiqing Sun, Yiming Yang. NeurIPS 2023 (spotlight)

§  Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision. Zhiqing Sun, Yikang Shen, Qinhong Zhou, Hongxin Zhang, Zhenfang Chen, David D. Cox, Yiming Yang, Chuang Gan. NeurIPS 2023 (spotlight)

§  Self-Refine: Iterative Refinement with Self-Feedback. Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Sean Welleck, Bodhisattwa Prasad Majumder, Shashank Gupta, Amir Yazdanbakhsh, Peter Clark. NeurIPS 2023

§  Generation-driven Contrastive Self-training for Zero-shot Text Classification with Instruction-tuned GPT. Ruohong Zhang, Yau-Shian Wang, Yiming Yang. CoRR abs/2304.11872 (2023)

§  Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning with LLMs. Pranjal Aggarwal, Aman Madaan, Yiming Yang, Mausam. EMNLP 2023.

§  Active Retrieval Augmented Generation. Zhengbao Jiang, Frank F. Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, Graham Neubig. EMNLP 2023.

§  CompleQA: Benchmarking the Impacts of Knowledge Graph Completion Methods on Question Answering. Donghan Yu, Yu Gu, Chenyan Xiong, Yiming Yang. Findings of EMNLP 2023

§  Accelerating Diffusion-based Combinatorial Optimization Solvers by Progressive Distillation. Junwei Huang, Zhiqing Sun, Yiming Yang.  ICML’2023 workshop.

§  Recitation-Augmented Language Models. Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, Denny Zhou.  ICLR 2023.

§  Long-tailed Extreme Multi-label Text Classification with Generated Pseudo Label Descriptions.  Ruohong Zhang, Yau-Shian Wang, Yiming Yang, Tom Vu, Likun Lei: EACL 2023.

2022

§  DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems.  Ruizhong Qiu*, Zhiqing Sun*, Yiming Yang: NeurIPS 2022.

§  Sparse Attention with Learning to Hash. Zhiqing Sun, Yiming Yang, Shinjae Yoo.  ICLR 2022

§  Exploiting Local and Global Features in Transformer-based Extreme Multi-label Text Classification. Ruohong Zhang, Yau-Shian Wang, Yiming Yang, Tom Vu, Likun Lei.  CoRR abs/2204.00933 (2022)

§  Memory-assisted prompt editing to improve GPT-3 after deployment. Aman Madaan*, Niket Tandon*, Peter Clark, and Yiming Yang: EM-NLP 2022.

§  Conditional set generation using Seq2seq model. Aman Madaan, Dheeraj Rajagopal, Niket Tandon, Yiming Yang, and Antoine Bosselu: EM-NLP 2022.

§  Language Models of Code are Few-Shot Commonsense Learners (CoCoGen). Aman Madaan, Shuyan Zhou, Uri Alon, Yiming Yang, Graham Neubig: EM-NLP 2022.

§  FLOWGEN: Fast and slow graph generation.  Aman Madaan, Yiming Yang.  Dynamic Neural Networks Workshop at ICML 2022.

§  Learning to Repair: Repairing model output errors after deployment using a dynamic memory of feedback. Niket Tandon*, Aman Madaan*, Peter Clark, and Yiming Yang: NAACL 2022 (Findings)

§  PAL: Program-aided Language Models. Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, Graham Neubig. CoRR abs/2211.10435 (2022)

§  JAKET: Joint Pre-training of Knowledge Graph and Language Understanding.  Donghan Yu, Chenguang Zhu, Yiming Yang, Michael Zeng.  AAAI 2022: 11630-11638

§  KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering. Donghan Yu, Chenguang Zhu, Yuwei Fang, Wenhao Yu, Shuohang Wang, Yichong Xu, Xiang Ren, Yiming Yang, Michael Zeng:  ACL (1) 2022: 4961-4974

2021

§  Rethinking Transformer-based Set Prediction for Object Detection. [pdf] Zhiqing Sun, Shengcao Cao, Yiming Yang, Kris Kitani.  ICCV 2021.

§  Enhancing Summarization with Text Classification via Topic Consistency [pdf] Jingzhou Liu and Yiming Yang. ECML 2021.

§  Unsupervised Extractive Text Summarization with Distance-Augmented Sentence Graphs. [pdf] Jingzhou Liu, Dominic J. D. Hughes, Yiming Yang. SIGIR 2021: 2313-2317

§  Could you give me a hint? Generating inference graphs for defeasible reasoning. [pdf] Aman Madaan, Dheeraj Rajagopal, Niket Tandon, Yiming Yang, Eduard H. Hovy. ACL/IJCNLP (Findings) 2021: 5138-5147.

§  Meta Back-translation [pdf] Hieu Pham, Xinyi Wang, Yiming Yang, Graham Neubig. ICLR 2021.

§  Generalized Multi-Relational Graph Convolution Networks [pdf]  Donghan Yu, Yiming Yang, Ruohong Zhang, Yuexin Wu. WWW 2021.

§  Neural language modeling for contextualized temporal graph generation [pdf] Aman Madaan and Yiming Yang.  NAACL 2021

2020

• Graph-Revised Convolutional Network [pdf] Donghan Yu, Ruohong Zhang, Zhengbao Jiang, Yuexin Wu, Yiming Yang.  ECML-PKDD 2020
• Correlation-Aware Change-Point Detection via Graph Neural Networks [pdf] Ruohong Zhang, Yu Hao, Donghan Yu, Wei-Cheng Chang, Guokun Lai, Yiming Yang International Conference on Neural Information Processing, 555-567 2020 Item Recommendation for Word-of-Mouth Scena (ICONIP) 2020: 555-567
• Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing [pdf] Guokun Lai*, Zihang Dai*, Yiming Yang, Quoc Le NeurLPS 2020
• VIOLIN: A Large-Scale Dataset for Video-and-Language Inference [pdf] Jingzhou Liu, Wenhu Chen, Yu Cheng, Zhe Gan, Licheng Yu, Yiming Yang Conference on Computer Vision and Pattern Recognition (CVPR), 2020
• Going Beyond Token-level Pre-training for Embedding-based Large-scale Retrieval [pdf] Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar. ICLR 2020
• Taming Pre-trained Transformers for eXtreme Multi-label Text Classification [pdf] Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, Inderjit S. Dhillon. KDD 2020
• Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework [pdf] Zirui Wang, Jiateng Xie, Ruochen Xu, Yiming Yang, Graham Neubig, Jaime G. Carbonell. ICLR 2020
• MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices [pdf] Zhiqing Sun, Hongkun Yu, Xiaodan Song, Renjie Liu, Yiming Yang, Denny Zhou. Association for Computational Linguistics (ACL), 2020.
• An EM Approach to Non-autoregressive Conditional Sequence Generations [pdf] Zhiqing Sun Yiming Yang. International Conference on Machine Learning (ICML), 2020.
• A Re-evaluation of Knowledge Graph Completion Methods [pdf] Zhiqing Sun, Shikhar Vashishth, Soumya Sanyal, Partha Talukdar, Yiming Yang Association for Computational Linguistics (ACL), 2020 (Short Paper)
• Predicting Performance for Natural Language Processing [pdf] Mengzhou Xia, Antonios Anastasopoulos, Ruochen Xu, Yiming Yang and Graham Neubig. Association for Computational Linguistics (ACL), 2020
• Politeness Transfer: A Tag and Generate Approach [pdf] Aman Madaan, Amrith Setlur, Tanmay Parekh, Barnabas Poczos, Graham Neubig, Yiming Yang, Ruslan Salakhutdinov, Alan W Black and Shrimai Prabhumoye. Association for Computational Linguistics (ACL), 2020

2019

• Re-examination of the Role of Latent Variables in Sequence Modeling [pdf] Guokun Lai, Zihang Dai, Yiming Yang, Shinjae Yoo NeurLPS 2019: 7812-7822
• XLNet: Generalized Autoregressive Pretraining for Language Understanding [pdf] Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Quoc V. Le, Ruslan Salakhutdinov. NeurLPS 2019: 5754-5764
• Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context. [pdf] Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc V. Le, Ruslan Salakhutdinov. ACL 2019
• Implicit Kernel Learning [pdf] Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos. AISTATS 2019
• Kernel Change-point Detection with Auxiliary Deep Generative Models [pdf] Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos. ICLR 2019
• DARTS: Differentiable Architecture Search [pdf] Hanxiao Liu, Karen Simonyan, Yiming Yang. ICLR 2019
• Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning [pdf] Yuexin Wu, Jingjing Liu, Jiangfeng Gao, Yiming Yang.  AAAI 2019

2018

• Low-resource Cross-lingual Event Type Detection via Distant Supervision with Minimal Effort. [pdf] Aldrian Obaja Muis, Naoki Otani, Nidhi Vyas, Ruochen Xu, Yiming Yang, Teruko Mitamura, Eduard H. Hovy  COLING 2018: 70-82
• Unsupervised Cross-lingual Transfer of Word Embedding Spaces [pdf] Ruochen Xu Yiming Yang, Naoki Otani, Yuexin Wu. EMNLP 2018: 2465-2474
• Modeling Long-and Short-Term Temporal Patterns with Deep Neural Networks [pdf] Guokun Lai, Wei-Cheng Chang, Yiming Yang, Hanxiao Liu. SIGIR 2018: 95-104
• Deep Learning for Epidemiological Predictions [pdf] Yuexin Wu, Yiming Yang, Hanxiao Liu. SIGIR 2018: 1085-1088
• Graph Convolutional Matrix Completion for Bipartite Edge Prediction [pdf] Yuexin Wu, Hanxiao Liu, Yiming Yang. KDIR 2018:49-58
• Learning Graph Convolution Filters from Data Manifold [pdf] Guokun Lai, Hanxiao Liu, Yiming Yang. ICML 2018 Workshop on Theoretical Foundations and Applications of Deep Generative Models
• Stochastic WaveNet: A Generative Latent Variable Model for Sequential Data [pdf] Guokun Lai, Bohan Li, Guoqing Zheng, Yiming Yang. ICML 2018 Workshop on on Theoretical Foundations and Applications of Deep Generative Models
• Convolutional Normalizing Flows [pdf] Guoqing Zheng, Yiming Yang, Jaime Carbonell. ICML 2018 Workshop on on Theoretical Foundations and Applications of Deep Generative Models
• Asymmetric Variational Autoencoders [pdf] Guoqing Zheng, Yiming Yang, Jaime Carbonell. ICML 2018 Workshop on Theoretical Foundations and Applications of Deep Generative Models
• The ARIEL-CMU situation frame detection pipeline for LoReHLT16: a model translation approach [URL] Patrick Littell, Tian Tian, Ruochen Xu, Zaid Sheikh, David R. Mortensen, Lori S. Levin, Francis Tyers, Hiroaki Hayashi, Graham Horwood, Steve Sloto, Emily Tagtow, Alan W. Black, Yiming Yang, Teruko Mitamura, Eduard H. Hovy
  Machine Translation 32(1-2): 105-126 (2018)

2017

• MMD GAN: Towards Deeper Understanding of Moment Matching Network [pdf] Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang. NIPS 2017
• RACE: Large-scale ReAding Comprehension Dataset From Examinations [pdf] Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, Eduard H. Hovy. EMNLP 2017
• Cross-lingual Distillation for Text Classification [pdf] Ruochen Xu, Yiming Yang. ACL 2017: 1415-1425
• Analogical Inference for Multi-relational Embeddings [web] Hanxiao Liu, Yuexin Wu, Yiming Yang. ICML 2017: 2168-2178
• Data-driven Random Fourier Features using Stein Effect [web] Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos. IJCAI 2017: 1497-1503
• Deep Learning for Extreme Multi-label Text Classification [web] Jingzhou Liu, Wei-Cheng Chang, Yuexin Wu, Yiming Yang. SIGIR 2017: 115-124
• Experiments in Curation: Towards Machine-Assisted Construction of Software Architecture Knowledge Bases [web] Ian Gorton, Ruochen Xu, Yiming Yang, Hanxiao Liu, Guoqing Zheng. ICSA 2017: 79-88
• Cross-Domain Kernel Induction for Transfer Learning [web] Wei-Cheng Chang, Yuexin Wu, Hanxiao Liu, Yiming Yang. AAAI 2017: 1763-1769

2016

• Leveraging Multilingual Training for Limited Resource Event Extraction [pdf] Andrew Hsi, Yiming Yang, Jaime Carbonell and Ruochen Xu. International Conference on Computational Linguistics (COLING 2016): 1201-1210
• Adaptive Smoothed Online Multi-Task Learning [pdf] Hanxiao Liu*, Keerthiram Murugesan*, Jaime G. Carbonell, Yiming Yang. Neural Information Processing Systems, NIPS 2016, Barcelona, Spain.
• Cross-lingual Text Classification via Model Translation with Limited Dictionaries [pdf] Ruochen Xu, Yiming Yang, Hanxiao Liu, Andrew His. ACM Information and Knowledge Management (CIKM) 2016: 95-104.
• Data-driven Automated Induction of Prerequisite Structure Graphs [pdf] Devendra Singh Chaplot, Yiming Yang, Jaime Carbonell and Kenneth R. Koedinger. The 9th Intl. Conf. on Educational Data Mining (EDM 2016), Raleigh, North Carolina, USA.
• Efficient Shift-Invariant Dictionary Learning [web] Guoqing Zheng, Yiming Yang, Jaime Carbonell. The 22nd ACM SIGKDD Conference (KDD 2016), San Francisco, CA.
• Cross-Graph Learning of Multi-Relational Associations [pdf] Hanxiao Liu and Yiming Yang. International Conference on Machine Learning (ICML) 2016, New York City, USA.
• Semi-supervised Learning with Adaptive Spectral Transform [web] Hanxiao Liu and Yiming Yang. Artificial Intelligence and Statistics (AISTATS) 2016, Cádiz, Spain.
• Learning Concept Graphs from Online Educational Data [pdf] Hanxiao Liu, Wanli Ma, Yiming Yang and Jaime Carbonell. J. J. Artif. Intell. Res. (JAIR) 55: 1059-1090 (2016).

2015

• Bipartite Edge Prediction via Transductive Learning over Product Graphs [pdf][supplementary] Hanxiao Liu and Yiming Yang. ICML 2015
• Concept Graph Learning from Educational Data [web] Yiming Yang, Hanxiao Liu, Jaime Carbonell and Wanli Ma. The Eighth International Conference on Web Search and Data Mining (WSDM), 2015

2014

• Transformation-based Probabilistic Clustering with Supervision [pdf] [supplementary].  Siddharth Gopal, Yiming Yang. UAI 2014
• Von Mises-Fisher clustering models [pdf][supplementary] Siddharth Gopal, Yiming Yang. ICML 2014

2013

• Recursive regularization for large-scale classification with hierarchical and graphical dependencies [pdf].  Siddharth Gopal, Siddharth Gopal, Yiming Yang. SIGKDD 2013 [Best student paper runner up]
• Distributed training of large-scale logistic models [pdf] Siddharth Gopal, Yiming Yang. ICML 2013

2012

• Bayesian models for large-scale hierarchical classification [pdf][supplementary] Siddharth Gopal, Yiming Yang, Bing Bai, Alexandru Niculescu-Mizil. NIPS 2012
• A unified optimization framework for auction and guaranteed delivery in online advertising [pdf] Konstantin Salomatin, Tie-Yan Liu, Yiming Yang. CIKM 2012
• A Regularization Framework for Large-scale Hierarchical Classification [pdf] Siddharth Gopal, Yiming Yan, Alexandru Niculescu-Mizil. Large-scale Hierarchical Text Classification Challenge - ECML 2012
• Multilabel Classification with meta-level features in a learning-to-rank framework [pdf] Yiming Yang and Siddharth Gopal. Machine Learning, DOI: 10.1007/s10994-011-5270-7.

2011

• Modeling personalized email prioritization: classification-based and regression-based approaches [pdf] Shinjae Yoo, Yiming Yang, Jaime G. Carbonell
  CIKM 2011: 729-738
• Statistical learning for file-type identification [pdf] Siddharth Gopal, Yiming Yang, Konstantin Salomatin and Jaime Carbonell. International Conference of Machine Learning Applications (ICMLA), 2011.

2010

• Learning to rank relevant and novel documents through user feedback [pdf] Abhimanyu Lad and Yiming Yang. CIKM 2010
• CiteData: A new multi-faceted dataset for evaluating personalized search performance [pdf] Abhay Harpale, Yiming Yang, Siddharth Gopal, Daqing He and Zhen Yue. CIKM 2010
• Active Learning for Multi-Task Adaptive Filtering [pdf] Abhay Harpale and Yiming Yang. ICML 2010
• Personalized email prioritization based on content and social network analysis. Yiming Yang, Shinjae Yoo, Frank Lin and II-Chul Moon. IEEE Intelligent Systems: Special Issue on Social Learning,Vol. 25(4), pp12-18, July/August 2010.
• Active Ordering of Interactive Prediction Tasks [pdf] Abhimanyu Lad, Yiming Yang. SDM 2010: 537-547
• Multi-label classification with meta-level features [pdf] Siddharth Gopal, Yiming Yang. SIGIR 2010: 315-322

2009

• Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling [pdf] Yiming Yang,  Abhay Harpale and Subramaniam Ganapathyand. The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2009
• Modeling Expected Utility of Multi-session Information Distillation [pdf] Yiming Yang and Abhimanyu Lad.  Second International Conference on the Theory of Information Retrieval (ICTIR09), 2009
• Mining Social Networks for Personalized Email Prioritization [pdf] Shinjae Yoo, Yiming Yang, Frank Lin and Il-Chul Moon. The 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD09), 2009
• Toward Optimal Ordering of Prediction Tasks [pdf] Abhimanyu Lad, Yiming Yang, Rayid Ghani and Bryan Kisiel. SIAM International Conference on Data Mining (SDM09), pp 883-893, 2009
• Toward Optimal Ordering of Prediction Tasks [pdf] Konstantin Salomatin, Yiming Yang and Abhimanyu Lad. Multi-field Correlated Topic Modeling (pdf). SIAM International Conference on Data Mining (SDM09), pp 628-637, 2009

2008

• Personalized Active Learning for Collaborative Filtering [pdf] Abhay Harpale and Yiming Yang. ACM SIGIR’08: 91-98
• Scholarpedia: Text Categorization [web] Yiming Yang and Thorsten Joachims (2008) Text categorization. 3(5):4242
• Flexible Latent Variable Models for Multi-Task Learning Flexible Latent Variable Models for Multi-Task Learning [pdf] Jian Zhang, Zoubin Ghahramani and Yiming Yang.  Machine Learning, 2008

2007

• Generalizing from Relevance Feedback using Named Entity Wildcards [pdf] Abhimanyu Lad, Yiming Yang. CIKM 2007
• Utility-based information distillation over temporally sequenced documents [pdf] Yiming Yang, Abhimanyu Lad, Ni Lao, Abhay Harpale, Bryan Kisiel, Monica Rogati, Jian Zhang, Jaime Carbonell, Peter Brusilovsky, Daqing He. SIGIR 2007: 31-38

2005

• Robustness of Adaptive Filtering Methods in a Cross-benchmark Evaluation [pdf] Yiming Yang, Shinjae Yoo, Jian Zhang and Bryan Kisiel. ACM SIGIR 2005.
• Learning Multiple Related Tasks using Latent Independent Component Analysis [pdf] Jian Zhang, Zoubin Ghahramani and Yiming Yang.  NIPS 2005
• From lasso regression to feature vector machine [pdf] Fan Li, Yiming Yang, Eric P. Xing. NIPS 2005
• Use modified lasso regressions to learn large undirected graphs in a probabilistic framework [pdf] Fan Li, Yiming Yang.  AAAI 2005.
• Support Vector Machines Classification with Very Large-Scale Taxonomy [pdf]. Tie-Yan Liu, Yiming Yang, Hao Wan, et al. SIGKDD Explorations, Special Issue on Text Mining and Natural Language Processing, vol.7, issue.1, pp36~43, 2005
• Analysis of recursive gene selection approaches from micro-array data (MEDLINE indexed) [web] Fan Li, Yiming Yang. Journal Bioinformatics, 2005
• Using recursive classification to discover predictive features [pdf]. Fan Li, Yiming Yang. ACM SAC 2005

2004

• A Probabilistic Model for Online Document Clustering with Application to Novelty Detection [pdf] Jian Zhang, Zoubin Ghahramani and Yiming Yang. NIPS 2004, Vancouver, Canada, 2004
• Resource Selection for Domain Specific CLIR [pdf] Monica Rogati and Yiming Yang. ACM SIGIR 2004
• Probabilistic Score Estimation with Piecewise Logistic Regression [pdf] Jian Zhang and Yiming Yang. ICML 2004
• The Enron Corpus: A New Dataset for Email Classification Research [pdf] B. Klimt and Yiming Yang. ECML 2004
• Learning Table Extraction from Examples [pdf] Tengli, Yiming Yang and N. Ma. COLING 2004
• Applying CLIR Techniques to Event Tracking [pdf] Niangli Ma, Yiming Yang & Monica  Rogati.  Lecture Notes in Computer Science. Revised Selected Papers, Information Retrieval Technology: Asia Information Retrieval Symposium (AIRS), 2004
• RCV1: A New Benchmark Collection for Text Categorization Research [pdf]. David Lewis, Yiming Yang, Tony Rose and Fan Li. Journal of Machine Learning Research 5 (2004) 361-397

2003

• Margin-based Local Regression of Adaptive Filtering [pdf] Yiming Yang and Bryan Kisiel. ACM CIKM 2003
• A scalability analysis of classifiers in text categorization [pdf] Yiming Yang, Jian Zhang and Byan Kisiel. ACM SIGIR'03, pp 96-103, 2003
• A loss function analysis for classification methods in text categorization [pdf] Fan Li and Yiming Yang, ICML 2003, pp472-479, 2003
• Robustness of regularized linear classification methods in text categorization [pdf] Jian Zhang and Yiming Yang. ACM SIGIR'03, pp 190-197, 2003
• Modified logistic regression: an approximation to SVM and its application in large-scale text categorization [pdf] Jian Zhang, Rong Jing, Yiming Yang and A. Hauptmann.  ICML'03, pp888-897, 2003
• Unsupervised learning of Arabic stemming using a parallel corpus [pdf] Monica Rogati, Scott McCarley and Yiming Yang. ACL'03 pp391-398, 2003

2002

• Topic-conditioned Novelty Detection [pdf] Yiming Yang, Jian Zhang, Jaime Carbonell and Chun Jin. ACM SIGKDD Internaltional Conference on Knowledge Discovery and Data Mining, pp 688-693, 2002
• Stochastic Link and Group Detection [pdf] Jeremy Kubica, Andrew Moore, Jeff Schneider and Yiming Yang. AAAI-02, 2002
• A study of approaches to hypertext categorization [pdf] Yiming Yang, S. Slattery and R. Ghani. Journal of Intelligent Information Systems, Volume 18, Number 2, March 2002
• High-performing feature selection for text classification [pdf] M. Rogati and Yiming Yang. ACM CIKM 2002

2001

• kNN, Rocchio and Metrics for Information Filtering at TREC-10 [pdf] Thomat Ault and Yiming Yang. TREC-10 Notes, Nov. 2001
• Hypertext categorization using hyperlink patterns and meta data [pdf] Rayid Ghani, Sean Slattery and Yiming Yang. ICML'01, pp 178-185, 2001
• A study on thresholding strategies for text categorization [pdf] Yiming Yang. SIGIR'01, pp 137-145, 2001
• Cross-Lingual Pseudo-Relevance Feedback Using a Comparable Corpus [pdf] Monica Rogati and Yiming Yang. CLEF'01, 2001

2000

• Improving text categorization methods for event tracking [pdf] Yiming Yang, Thomas Ault, Thomas Pierce and Charles W Lattimer. SIGIR'00, pp65-72. 2000
• Combining multiple learning strategies for effective cross validation [pdf] Yiming Yang, Thomas Ault, Thomas Pierce. ICML'00, pp1167-1182, 2000

1999

• Learning Approaches for Detecting and Tracking News Events [pdf] Yiming Yang, Jaime Carbonell, Ralf Brown, Thomas Pierce, Brian T. Archibald, Xin Liu. IEEE Intelligent Systems: Special Issue on Applications of Intelligent Information Retrieval,Vol. 14(4), pp32-43, July/August 1999
• A re-examination of text categorization methods [pdf] Yiming Yang and Xin Liu. SIGIR'99, pp 42--49, 1999
• An evaluation of statistical approaches to text categorization [pdf] Yiming Yang. Journal of Information Retrieval, Vol 1, No. 1/2, pp 67--88, 1999

1998

• CONALD Report on the Workshop on Learning from Text and the Web [pdf] Carbonell J., Craven M., Fienberg S., Mitchell T. and Yang Y. June, 1998
• Topic Detection and Tracking Pilot Study Final Report [pdf] James Allan, Jaime Carbonell, Doddington, G., Yamron, J. and Yiming Yang.
  Proceedings of the Broadcast News Transcription and Understranding Workshop (Sponsored by DARPA), Feb. 1998
• Translingual Information Retrieval: Learning from Bilingual Corpora [pdf] Yiming Yang., Carbonell, J. G., Brown, R. and Frederking, R. E.
  Artificial Intelligence Journal special issue: Best of IJCAI-97, 1998, pp323--345
• A Study on Retrospective and On-line Event Detection [pdf] Yiming Yang, Pierce, T., Carbonell, J. G. SIGIR'98

1997

• Translingual Information Retrieval: a comparative evaluation [pdf] Carbonell, J. G., Yiming Yang.,. Frederking, R. E., Brown, R., Geng, Y., and Lee, D.
  Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'97 Distinguished Paper Award), 1997
• A Comparative Study on Feature Selection in Text Categorization [pdf] Yiming Yang, Pedersen J.P. Proceedings of the Fourteenth International Conference on Machine Learning (ICML'97), 1997, pp412-420
• An Evaluation of statistical approach to text categorization [pdf] Yiming Yang. Technical Report CMU-CS-97-127, Computer Science Department, Carnegie Mellon University, 1997

1996

• Sampling strategies and learning efficiency in text categorization [pdf] Yiming Yang. AAAI Spring Symposium on Machine Learning in Information Access. 1996:88-95
• Using corpus statistics to remove redundant words in text categorization [pdf] Yiming Yang, John W. Wilbur. J Amer Soc Inf Sci. (JASIS) 1996
• An evaluation of a statistical approaches to MEDLINE indexing. Yiming Yang. J Proceedings of the 1996 Annual Full Symposium of the American Medical Informatics Association (AMIA), 1996:358-362

1995

• Noise Reduction in a Statistical Approach to Text Categorization [pdf] Yiming Yang. SIGIR'95, 1995:256-263, 1995.

1994

• An example-based mapping method for text classification and retrieval [pdf] Yiming Yang, Chris G. Chute. ACM Transactions on Information Systems (TOIS) 1994;12(3):252-77
• Expert Network: Effective and efficient learning from human decisions in text categorization and retrieval [pdf] Yiming Yang. SIGIR'94, pp11-21, 1994.
• An application of Expert Network to clinical classification and MEDLINE indexing. Yiming Yang, Chris G. Chute. Proceedings of the 18th Annual Symposium on Computer Applications in Medical Care (SCAMC'94). JAMIA 1994;18(Symp.Suppl):157-61 (Best Theoretical Paper Award)

1993

• Words or concepts: The features of indexing units and their optimal use in information retrieval. Yiming Yang, Chris G. Chute. Proceedings of 17th Annual Symposium on Computer Applications in Medical Care (SCAMC'93), 1993;17:685-9 (Best Theoretical Paper Award)
• An application of Least Squares Fit mapping to text information retrieval [pdf] Yiming Yang, Chris G. Chute. Proceedings of 16th Ann Int ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'93) 1993;281-90.

1992

• A Linear Least Squares Fit method for terminology mapping [pdf] Yiming Yang, Chris G. Chute. Proceedings of Fifteenth International Conference on Computational Linguistics (COLING'92), 1992;II:447-53