My Semantic Scholar and Google Scholar pages


  1. ACL
    Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions
    Haw-Shiuan Chang, and Andrew McCallum
    In Annual Meeting of the Association for Computational Linguistics (ACL) 2022


  1. EACL Oral
    Changing the Mind of Transformers for Topically-Controllable Language Generation
    Haw-Shiuan Chang, Jiaming Yuan, Mohit Iyyer, and Andrew McCallum
    In Conference of the European Chapter of the Association for Computational Linguistics (EACL) (Oral) 2021
  2. EACL Oral
    Multi-facet Universal Schema
    Rohan Paul*,  Haw-Shiuan Chang*, and Andrew McCallum
    In Conference of the European Chapter of the Association for Computational Linguistics (EACL) (Oral) 2021
  3. AAAI
    Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications
    Haw-Shiuan Chang, Amol Agrawal, and Andrew McCallum
    In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2021
  4. EMNLP Short
    Open Aspect Target Sentiment Classification with Natural Language Prompts
    Ronald Seoh*, Ian Birle*, Mrinal Tak*,  Haw-Shiuan Chang*, Brian Pinette, and Alfred Hough
    In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP) 2021


  1. ML
    Using Error Decay Prediction to Overcome Practical Issues of Deep Active Learning for Named Entity Recognition
    Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, and Andrew McCallum
    Machine Learning 2020
  2. KDD
    AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
    Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao,  Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, and Jiawei Han
    In KDD ’20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020 2020
  3. JCIM
    Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks
    Edward Kim, Zach Jensen, Alexander Grootel, Kevin Huang, Matthew Staib, Sheshera Mysore,  Haw-Shiuan Chang, Emma Strubell, Andrew McCallum, Stefanie Jegelka, and Elsa Olivetti
    J. Chem. Inf. Model. 2020


  1. LAW
    The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures
    Sheshera Mysore, Zach Jensen, Edward Kim, Kevin Huang,  Haw-Shiuan Chang, Emma Strubell, Jeffrey Flanigan, Andrew McCallum, and Elsa Olivetti
    In Proceedings of the 13th Linguistic Annotation Workshop at ACL 2019


  1. TMM
    Active Learning for Crowdsourced QoE Modeling
    Haw-Shiuan Chang, Chih-Fan Hsu, Tobias Hoßfeld, and Kuan-Ta Chen
    IEEE Trans. Multim. 2018
  2. NAACL
    Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection
    Haw-Shiuan Chang, ZiYun Wang, Luke Vilnis, and Andrew McCallum
    In Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (HLT/NAACL) 2018
  3. TextGraphs
    Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings
    Haw-Shiuan Chang, Amol Agrawal, Ananya Ganesh, Anirudha Desai, Vinayak Mathur, Alfred Hough, and Andrew McCallum
    In TextGraphs-12: the Workshop on Graph-based Methods for Natural Language Processing (NAACL WS) 2018


  1. NIPS
    Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples
    Haw-Shiuan Chang, Erik G. Learned-Miller, and Andrew McCallum
    In Advances in Neural Information Processing Systems (NIPS) 2017
  2. NIPS WS
    Automatically Extracting Action Graphs from Materials Science Synthesis Procedures
    Sheshera Mysore, Edward Kim, Emma Strubell, Ao Liu,  Haw-Shiuan Chang, Srikrishna Kompella, Kevin Huang, Andrew McCallum, and Elsa Olivetti
    In Workshop on Machine Learning for Molecules and Materials at NIPS 2017


  1. TAC/KBP
    Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema
    Haw-Shiuan Chang, Abdurrahman Munir, Ao Liu, Johnny Tian-Zheng Wei, Aaron Traylor, Ajay Nagesh, Nicholas Monath, Patrick Verga, Emma Strubell, and Andrew McCallum
    In Text Analysis Conference, Knowledge Base Population (TAC/KBP) 2016


  1. EDM Short
    Modeling Exercise Relationships in E-Learning: A Unified Approach
    Haw-Shiuan Chang, Hwai-Jung Hsu, and Kuan-Ta Chen
    In International Conference on Educational Data Mining (EDM) 2015
  2. CVIU
    Optimizing the Decomposition for Multiple Foreground Cosegmentation
    Haw-Shiuan Chang, and Yu-Chiang Frank Wang
    Computer Vision and Image Understanding (CVIU) 2015


  1. ACCV
    Simple-to-Complex Discriminative Clustering for Hierarchical Image Segmentation
    Haw-Shiuan Chang, and Yu-Chiang Frank Wang
    In Asian Conference on Computer Vision (ACCV) 2014


  1. ICIP
    Superpixel-based Large Displacement Optical Flow
    Haw-Shiuan Chang, and Yu-Chiang Frank Wang
    In IEEE International Conference on Image Processing, ICIP 2013
  2. TIP
    Exploring Visual and Motion Saliency for Automatic Video Object Extraction
    Wei-Te Li,  Haw-Shiuan Chang, Kuo-Chin Lien, Hui-Tang Chang, and Yu-Chiang Frank Wang
    IEEE Transactions on Image Processing 2013