@inproceedings{chang2022softmax,title={Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions},abbr={ACL},selected={true},bibtex_show={true},author={Chang, Haw-Shiuan and McCallum, Andrew},booktitle={Annual Meeting of the Association for Computational Linguistics (ACL)},year={2022},paper={https://aclanthology.org/2022.acl-long.554.pdf},code={https://aclanthology.org/attachments/2022.acl-long.554.software.zip},poster={ACL2022_poster.pdf},slides={ACL2022_slides.pdf},video={https://screencast-o-matic.com/watch/c3fresVYo4M}}
2021
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
@inproceedings{chang2021changing,title={Changing the Mind of Transformers for Topically-Controllable Language Generation},abbr={EACL Oral},selected={true},bibtex_show={true},author={Chang, Haw-Shiuan and Yuan, Jiaming and Iyyer, Mohit and McCallum, Andrew},booktitle={Conference of the European Chapter of the Association for Computational Linguistics (EACL) (Oral)},year={2021},paper={https://arxiv.org/abs/2103.15335},code={https://github.com/iesl/interactive_LM},video={https://slideslive.com/38954487/changing-the-mind-of-transformers-for-topicallycontrollable-language-generation},poster={proj1-nlp-interactive_LM-EACL_interactive_LM-poster.pdf},slides={proj1-nlp-interactive_LM-EACL_interactive_LM-slides.key}}
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
@inproceedings{chang2021multi-facet,title={Multi-facet Universal Schema},abbr={EACL Oral},bibtex_show={true},author={Paul*, Rohan and Chang*, Haw-Shiuan and McCallum, Andrew},booktitle={Conference of the European Chapter of the Association for Computational Linguistics (EACL) (Oral)},year={2021},paper={https://arxiv.org/abs/2103.15339},code={https://github.com/rohanpaul11/multifacet-re},video={https://slideslive.com/38954382/multifacet-universal-schema},poster={proj2-nlp-Multi-facet RE-EACL_multi-facet_RE_small-poster.pdf},slides={proj2-nlp-Multi-facet RE-EACL_multi-facet_RE_small-slides.key}}
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
@inproceedings{chang2021extending,title={Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications},abbr={AAAI},bibtex_show={true},author={Chang, Haw-Shiuan and Agrawal, Amol and McCallum, Andrew},booktitle={Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)},year={2021},paper={https://arxiv.org/abs/2103.15330},poster={proj3-nlp-Multi-facet Embeddings for Sentence Representation-poster.pdf},slides={https://docs.google.com/presentation/d/1k-OBWdBYsGmXUuvNc1_J_JrEppB_Aqh82bJPCgjFL-s/edit?usp=sharing}}
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
@inproceedings{Seoh_EMNLP_21,title={Open Aspect Target Sentiment Classification with Natural Language Prompts},abbr={EMNLP Short},bibtex_show={true},author={Seoh*, Ronald and Birle*, Ian and Tak*, Mrinal and Chang*, Haw-Shiuan and Pinette, Brian and Hough, Alfred},booktitle={Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)},paper={https://arxiv.org/abs/2109.03685},year={2021}}
2020
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
@article{chang2019ovecoming,abbr={ML},bibtex_show={true},selected={true},author={Chang, Haw-Shiuan and Vembu, Shankar and Mohan, Sunil and Uppaal, Rheeya and McCallum, Andrew},journal={Machine Learning},paper={http://arxiv.org/abs/1911.07335},title={Using Error Decay Prediction to Overcome Practical Issues of Deep Active Learning for Named Entity Recognition},year={2020},doi={10.1007/s10994-020-05897-1},publisher={Springer},video={https://slideslive.com/38933012/using-error-decay-prediction-to-overcome-practical-issues-of-deep-active-learning-for-named-entity-recognition},slides={https://docs.google.com/presentation/d/1h3bI1dS8-vS5ItcfGOHN3J7Wi7dnWWBf0gA4-yBXrk4/edit?usp=sharing}}
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
@inproceedings{DBLP:conf/kdd/DongHKLLMXZZSDM20,author={Dong, Xin Luna and He, Xiang and Kan, Andrey and Li, Xian and Liang, Yan and Ma, Jun and Xu, Yifan Ethan and Zhang, Chenwei and Zhao, Tong and Saldana, Gabriel Blanco and Deshpande, Saurabh and Manduca, Alexandre Michetti and Ren, Jay and Singh, Surender Pal and Xiao, Fan and Chang, Haw{-}Shiuan and Karamanolakis, Giannis and Mao, Yuning and Wang, Yaqing and Faloutsos, Christos and McCallum, Andrew and Han, Jiawei},abbr={KDD},bibtex_show={true},title={AutoKnow: Self-Driving Knowledge Collection for Products of Thousands
of Types},booktitle={{KDD} '20: The 26th {ACM} {SIGKDD} Conference on Knowledge Discovery
and Data Mining, Virtual Event, CA, USA, August 23-27, 2020},pages={2724--2734},publisher={{ACM}},year={2020},url={https://doi.org/10.1145/3394486.3403323},doi={10.1145/3394486.3403323},paper={https://arxiv.org/abs/2006.13473}}
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
@article{DBLP:journals/jcisd/KimJGHSMCSMJO20,author={Kim, Edward and Jensen, Zach and van Grootel, Alexander and Huang, Kevin and Staib, Matthew and Mysore, Sheshera and Chang, Haw{-}Shiuan and Strubell, Emma and McCallum, Andrew and Jegelka, Stefanie and Olivetti, Elsa},abbr={JCIM},bibtex_show={true},title={Inorganic Materials Synthesis Planning with Literature-Trained Neural
Networks},journal={J. Chem. Inf. Model.},volume={60},number={3},pages={1194--1201},year={2020},url={https://doi.org/10.1021/acs.jcim.9b00995},doi={10.1021/acs.jcim.9b00995},paper={https://arxiv.org/abs/1901.00032}}
2019
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
@inproceedings{mysore2019msannlaw,title={The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures},abbr={LAW},bibtex_show={true},author={Mysore, Sheshera and Jensen, Zach and Kim, Edward and Huang, Kevin and Chang, Haw-Shiuan and Strubell, Emma and Flanigan, Jeffrey and McCallum, Andrew and Olivetti, Elsa},booktitle={Proceedings of the 13th Linguistic Annotation Workshop at ACL},year={2019},paper={https://sigann.github.io/LAW-XIII-2019/pdf/W19-4007.pdf}}
2018
TMM
Active Learning for Crowdsourced QoE Modeling
Haw-Shiuan Chang, Chih-Fan Hsu, Tobias Hoßfeld, and Kuan-Ta Chen
@article{DBLP:journals/tmm/ChangHHC18,abbr={TMM},bibtex_show={true},author={Chang, Haw{-}Shiuan and Hsu, Chih{-}Fan and Ho{\ss}feld, Tobias and Chen, Kuan{-}Ta},title={Active Learning for Crowdsourced QoE Modeling},journal={{IEEE} Trans. Multim.},volume={20},number={12},pages={3337--3352},year={2018},paper={proj9-cv-Active Sampling for estimating QoE model-paper.pdf}}
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
@inproceedings{chang2017unsupervised,title={Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection},abbr={NAACL},bibtex_show={true},selected={true},author={Chang, Haw-Shiuan and Wang, ZiYun and Vilnis, Luke and McCallum, Andrew},booktitle={Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (HLT/NAACL)},paper={http://arxiv.org/abs/1710.00880},year={2018},code={https://github.com/iesl/Distributional-Inclusion-Vector-Embedding},poster={proj5-nlp-DIVE-poster.pdf},demo={https://bl.ocks.org/chsu5358/raw/f08d4755b0f04e113c139a72a977df5c/}}
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
@inproceedings{conf/TextGraph18/Chang18,abbr={TextGraphs},bibtex_show={true},author={Chang, Haw-Shiuan and Agrawal, Amol and Ganesh, Ananya and Desai, Anirudha and Mathur, Vinayak and Hough, Alfred and McCallum, Andrew},title={Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings},booktitle={TextGraphs-12: the Workshop on Graph-based Methods for Natural Language Processing (NAACL WS)},year={2018},slides={proj5-nlp-DIVE-slides.pdf},paper={https://arxiv.org/abs/1804.03257}}
2017
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
@inproceedings{DBLP:conf/nips/ChangLM17,abbr={NIPS},bibtex_show={true},selected={true},author={Chang, Haw{-}Shiuan and Learned{-}Miller, Erik G. and McCallum, Andrew},title={Active Bias: Training a More Accurate Neural Network by Emphasizing
High Variance Samples},booktitle={Advances in Neural Information Processing Systems (NIPS)},year={2017},poster={http://people.umass.edu/hawshiuancha/NIPS_poster_active_bias.pdf},paper={http://arxiv.org/abs/1704.07433}}
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
@inproceedings{mysore2017automatically,title={Automatically Extracting Action Graphs from Materials Science Synthesis Procedures},abbr={NIPS WS},bibtex_show={true},author={Mysore, Sheshera and Kim, Edward and Strubell, Emma and Liu, Ao and Chang, Haw-Shiuan and Kompella, Srikrishna and Huang, Kevin and McCallum, Andrew and Olivetti, Elsa},booktitle={Workshop on Machine Learning for Molecules and Materials at NIPS},year={2017},paper={https://arxiv.org/abs/1711.06872}}
2016
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
@inproceedings{DBLP:conf/tac/Chang16,abbr={TAC/KBP},bibtex_show={true},author={Chang, Haw-Shiuan and Munir, Abdurrahman and Liu, Ao and Wei, Johnny Tian-Zheng and Traylor, Aaron and Nagesh, Ajay and Monath, Nicholas and Verga, Patrick and Strubell, Emma and McCallum, Andrew},title={Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema},booktitle={Text Analysis Conference, Knowledge Base Population (TAC/KBP)},year={2016},paper={proj6-nlp-UMASS TAC 2016-paper.pdf}}
2015
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
@inproceedings{DBLP:conf/edm/ChangHC15,abbr={EDM Short},selected={true},bibtex_show={true},author={Chang, Haw{-}Shiuan and Hsu, Hwai{-}Jung and Chen, Kuan{-}Ta},title={Modeling Exercise Relationships in E-Learning: A Unified Approach},booktitle={International Conference on Educational Data Mining (EDM)},year={2015},paper={proj8-education-student modeling-paper.pdf},demo={https://drive.google.com/file/d/1V5nEwmVkPclj_ZR-bKt9xzW7ApT6ZJo-/view?usp=sharing},slides={proj8-education-student%20modeling-presentation.pptx},dataset={https://pslcdatashop.web.cmu.edu/DatasetInfo?datasetId=1198}}
CVIU
Optimizing the Decomposition for Multiple Foreground Cosegmentation
Haw-Shiuan Chang, and Yu-Chiang Frank Wang
Computer Vision and Image Understanding (CVIU) 2015
@article{CHANG201518,abbr={CVIU},bibtex_show={true},title={Optimizing the Decomposition for Multiple Foreground Cosegmentation},journal={Computer Vision and Image Understanding (CVIU)},volume={141},pages={18-27},year={2015},issn={1077-3142},doi={https://doi.org/10.1016/j.cviu.2015.06.004},url={https://www.sciencedirect.com/science/article/pii/S1077314215001320},author={Chang, Haw-Shiuan and Wang, Yu-Chiang Frank},code={http://mml.citi.sinica.edu.tw/papers/MFC_code_CVIU_2015},paper={proj11-cv-Decomposition of Multiple Foreground Co-segmentation-paper.pdf}}
2014
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
@inproceedings{DBLP:conf/accv/ChangW14,abbr={ACCV},bibtex_show={true},author={Chang, Haw{-}Shiuan and Wang, Yu{-}Chiang Frank},editor={Cremers, Daniel and Reid, Ian D. and Saito, Hideo and Yang, Ming{-}Hsuan},title={Simple-to-Complex Discriminative Clustering for Hierarchical Image
Segmentation},booktitle={Asian Conference on Computer Vision (ACCV)},series={Lecture Notes in Computer Science},volume={9005},pages={391--407},publisher={Springer},year={2014},url={https://doi.org/10.1007/978-3-319-16811-1\_26},doi={10.1007/978-3-319-16811-1\_26},code={http://mml.citi.sinica.edu.tw/papers/HDC_code_ACCV_2014/},paper={proj10-cv-Hierarchical Image Segmentation without Training-paper.pdf}}
2013
ICIP
Superpixel-based Large Displacement Optical Flow
Haw-Shiuan Chang, and Yu-Chiang Frank Wang
In IEEE International Conference on Image Processing, ICIP 2013
@inproceedings{DBLP:conf/icip/ChangW13,abbr={ICIP},bibtex_show={true},author={Chang, Haw{-}Shiuan and Wang, Yu{-}Chiang Frank},title={Superpixel-based Large Displacement Optical Flow},booktitle={{IEEE} International Conference on Image Processing, {ICIP}},pages={3835--3839},publisher={{IEEE}},year={2013},url={https://doi.org/10.1109/ICIP.2013.6738790},doi={10.1109/ICIP.2013.6738790},code={http://mml.citi.sinica.edu.tw/papers/SPLDOF_code.php},paper={proj12-cv-Superpixel-Based Large Displacement Optical Flow-paper.pdf}}
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
@article{6482623,abbr={TIP},bibtex_show={true},author={Li, Wei-Te and Chang, Haw-Shiuan and Lien, Kuo-Chin and Chang, Hui-Tang and Wang, Yu-Chiang Frank},journal={IEEE Transactions on Image Processing},title={Exploring Visual and Motion Saliency for Automatic Video Object Extraction},year={2013},volume={22},number={7},pages={2600-2610},doi={10.1109/TIP.2013.2253483},paper={pub-cv-tip2013-Exploring_Visual_and_Motion_Saliency_for_Automatic_Video_Object_Extraction.pdf}}