Publications

*indicates equal contribution, †indicates corresponding author

2025

1. TACL

   REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation by Extrapolating the Entropy of an Infinitely Large LM

   Haw-Shiuan Chang, Nanyun Peng, Mohit Bansal, Anil Ramakrishna, and Tagyoung Chung

   Transactions of the Association for Computational Linguistics (TACL), 2025

   Paper Bib Code

   @article{chang2025real,
     title = {REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation by Extrapolating the Entropy of an Infinitely Large LM},
     author = {Chang, Haw-Shiuan and Peng, Nanyun and Bansal, Mohit and Ramakrishna, Anil and Chung, Tagyoung},
     journal = {Transactions of the Association for Computational Linguistics (TACL)},
     year = {2025},
     paper = {https://arxiv.org/abs/2406.07735}
   }

2. EMNLP WS

   Latent Traits and Cross-Task Transfer: Deconstructing Dataset Interactions in LLM Fine-tuning

   Shambhavi Krishna, Atharva Naik, Chaitali Agarwal, Sudharshan Govindan, Haw-Shiuan Chang†, and Taesung Lee

   In Proceedings of *SEM 2025: The Fourteenth Joint Conference on Lexical and Computational Semantics (*SEM), 2025

   Paper Bib

   @inproceedings{naik2025latent,
     title = {Latent Traits and Cross-Task Transfer: Deconstructing Dataset Interactions in LLM Fine-tuning},
     author = {Krishna, Shambhavi and Naik, Atharva and Agarwal, Chaitali and Govindan, Sudharshan and Chang†, Haw-Shiuan and Lee, Taesung},
     booktitle = {Proceedings of *SEM 2025: The Fourteenth Joint Conference on Lexical and Computational Semantics (*SEM)},
     paper = {https://arxiv.org/abs/2509.13624},
     year = {2025}
   }

3. ACL WS Oral

   CoKe: Customizable Fine-Grained Story Evaluation via Chain-of-Keyword Rationalization

   Brihi Joshi, Sriram Venkatapathy, Mohit Bansal, Nanyun Peng, and Haw-Shiuan Chang

   In Proceedings of the Fourth Workshop on Natural Language Generation, Evaluation, and Metrics (GEM) (Oral), 2025

   Paper Bib

   @inproceedings{joshi2025coke,
     title = {CoKe: Customizable Fine-Grained Story Evaluation via Chain-of-Keyword Rationalization},
     author = {Joshi, Brihi and Venkatapathy, Sriram and Bansal, Mohit and Peng, Nanyun and Chang, Haw-Shiuan},
     booktitle = {Proceedings of the Fourth Workshop on Natural Language Generation, Evaluation, and Metrics (GEM) (Oral)},
     paper = {https://arxiv.org/abs/2503.17136},
     year = {2025}
   }

2024

1. EMNLP Oral

   Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM

   Haw-Shiuan Chang, Nanyun Peng, Mohit Bansal, Anil Ramakrishna, and Tagyoung Chung

   In Conference on Empirical Methods in Natural Language Processing (EMNLP) (Oral) (🏆 Best Paper Nomination from a Reviewer), 2024

   Paper Talk Bib Code Poster Slides

   @inproceedings{chang2024explaining,
     title = {Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM},
     author = {Chang, Haw-Shiuan and Peng, Nanyun and Bansal, Mohit and Ramakrishna, Anil and Chung, Tagyoung},
     booktitle = {Conference on Empirical Methods in Natural Language Processing (EMNLP) (Oral) (🏆 Best Paper Nomination from a Reviewer)},
     paper = {https://arxiv.org/abs/2411.01610},
     year = {2024}
   }

2. EMNLP Findings

   LLM Self-Correction with DeCRIM: Decompose, Critique, and Refine for Enhanced Following of Instructions with Multiple Constraints

   Thomas Palmeira Ferraz, Kartik Mehta, Yu-Hsiang Lin, Haw-Shiuan Chang, Shereen Oraby, Sijia Liu, Vivek Subramanian, Tagyoung Chung, Mohit Bansal, and Nanyun Peng

   In Findings of the Association for Computational Linguistics: EMNLP, 2024

   Paper Bib

   @inproceedings{ferraz2024llm,
     title = {LLM Self-Correction with DeCRIM: Decompose, Critique, and Refine for Enhanced Following of Instructions with Multiple Constraints},
     author = {Ferraz, Thomas Palmeira and Mehta, Kartik and Lin, Yu-Hsiang and Chang, Haw-Shiuan and Oraby, Shereen and Liu, Sijia and Subramanian, Vivek and Chung, Tagyoung and Bansal, Mohit and Peng, Nanyun},
     booktitle = {Findings of the Association for Computational Linguistics: EMNLP},
     paper = {https://arxiv.org/abs/2410.06458},
     year = {2024}
   }

3. EMNLP WS

   CS4: Measuring the Creativity of Large Language Models Automatically by Controlling the Number of Story-Writing Constraints

   Anirudh Atmakuru*, Jatin Nainani*, Rohith Siddhartha Reddy Bheemreddy*, Anirudh Lakkaraju*, Zonghai Yao, Hamed Zamani, and Haw-Shiuan Chang*

   In 6th Workshop on Narrative Understanding (WNU), 2024

   Paper Bib Code Poster

   @inproceedings{anirudh2024cs4,
     title = {CS4: Measuring the Creativity of Large Language Models Automatically by Controlling the Number of Story-Writing Constraints},
     author = {Atmakuru*, Anirudh and Nainani*, Jatin and Bheemreddy*, Rohith Siddhartha Reddy and Lakkaraju*, Anirudh and Yao, Zonghai and Zamani, Hamed and Chang*, Haw-Shiuan},
     booktitle = {6th Workshop on Narrative Understanding (WNU)},
     year = {2024},
     paper = {https://arxiv.org/abs/2410.04197},
   }

4. NAACL WS

   Fine-to-Coarse Entailment Hierarchy Construction for Coarse-to-Fine Story Generation

   Haw-Shiuan Chang, Nanyun Peng, Mohit Bansal, and Tagyoung Chung

   In Bridging Human-Computer Interaction and Natural Language Processing (HCI+NLP), 2024

   Paper Bib Poster Slides

   @inproceedings{chang2024fine,
     title = {Fine-to-Coarse Entailment Hierarchy Construction for Coarse-to-Fine Story Generation},
     author = {Chang, Haw-Shiuan and Peng, Nanyun and Bansal, Mohit and Chung, Tagyoung},
     booktitle = {Bridging Human-Computer Interaction and Natural Language Processing (HCI+NLP)},
     year = {2024},
     paper = {https://www.amazon.science/publications/fine-to-coarse-entailment-hierarchy-construction-for-coarse-to-fine-story-generation},
   }

5. WSDM

   To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential Recommenders

   Haw-Shiuan Chang, Nikhil Agarwal, and Andrew McCallum

   In Proceedings of The 17th ACM International Conference on Web Search and Data Mining, 2024

   Paper Bib Code Poster

   @inproceedings{chang2024copy,
     title = {To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential Recommenders},
     author = {Chang, Haw-Shiuan and Agarwal, Nikhil and McCallum, Andrew},
     booktitle = {Proceedings of The 17th ACM International Conference on Web Search and Data Mining},
     year = {2024},
     paper = {https://arxiv.org/abs/2310.14079},
   }

2023

1. ACL Findings

   Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond

   Haw-Shiuan Chang*, Zonghai Yao*, Alolika Gon, Hong Yu, and Andrew McCallum

   In Findings of the Association for Computational Linguistics: ACL 2023 (Findings of ACL), 2023

   Paper Talk Bib Code Poster Slides

   @inproceedings{chang2023revisiting,
     title = {Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond},
     author = {Chang*, Haw-Shiuan and Yao*, Zonghai and Gon, Alolika and Yu, Hong and McCallum, Andrew},
     booktitle = {Findings of the Association for Computational Linguistics: ACL 2023 (Findings of ACL)},
     year = {2023},
     paper = {http://arxiv.org/abs/2305.12289},
   }

2. ACL

   Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling

   Haw-Shiuan Chang*, Ruei-Yao Sun*, Kathryn Ricci*, and Andrew McCallum

   In Annual Meeting of the Association for Computational Linguistics (ACL), 2023

   Paper Talk Bib Code Poster Slides

   @inproceedings{chang2023multi-cls,
     title = {Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling},
     author = {Chang*, Haw-Shiuan and Sun*, Ruei-Yao and Ricci*, Kathryn and McCallum, Andrew},
     booktitle = {Annual Meeting of the Association for Computational Linguistics (ACL)},
     year = {2023},
     paper = {https://arxiv.org/abs/2210.05043},
   }

3. ArXiv

   Encoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens

   Ronald Seoh*, Haw-Shiuan Chang*, and Andrew McCallum

   arXiv preprint arXiv:2309.04333, 2023

   Paper Bib

   @article{seoh2023encoding,
     title = {Encoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens},
     author = {Seoh*, Ronald and Chang*, Haw-Shiuan and McCallum, Andrew},
     journal = {arXiv preprint arXiv:2309.04333},
     year = {2023},
     paper = {https://arxiv.org/abs/2309.04333}
   }

2022

1. Thesis

   Modeling the Multi-mode Distribution in Self-Supervised Language Models

   Haw-Shiuan Chang

   In PhD Thesis, 2022

   Paper Bib Slides

   @inproceedings{chang2022modeling,
     title = {Modeling the Multi-mode Distribution in Self-Supervised Language Models},
     author = {Chang, Haw-Shiuan},
     booktitle = {PhD Thesis},
     year = {2022},
     paper = {https://web.archive.org/web/20221031171926id_/https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=3783&context=dissertations_2},
   }

2. 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

   Paper Talk Bib Code Poster Slides

   @inproceedings{chang2022softmax,
     title = {Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions},
     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},
   }

3. SDP

   Unsupervised Partial Sentence Matching for Cited Text Identification

   Kathryn Ricci*, Haw-Shiuan Chang*, Purujit Goyal, and Andrew McCallum

   In Proceedings of the Third Workshop on Scholarly Document Processing, 2022

   Paper Bib

   @inproceedings{ricci2022unsupervised,
     title = {Unsupervised Partial Sentence Matching for Cited Text Identification},
     author = {Ricci*, Kathryn and Chang*, Haw-Shiuan and Goyal, Purujit and McCallum, Andrew},
     booktitle = {Proceedings of the Third Workshop on Scholarly Document Processing},
     pages = {95--104},
     year = {2022},
     paper = {https://aclanthology.org/2022.sdp-1.11.pdf}
   }

4. NAACL WS

   Augmenting Scientific Creativity with Retrieval across Knowledge Domains

   Hyeonsu B. Kang*, Sheshera Mysore*, Kevin Huang*, Haw-Shiuan Chang, Thorben Prein, Andrew McCallum, Aniket Kittur, and Elsa Olivetti

   In Bridging Human-Computer Interaction and Natural Language Processing (HCI+NLP), 2022

   Paper Bib

   @inproceedings{kang2022augmenting,
     title = {Augmenting Scientific Creativity with Retrieval across Knowledge Domains},
     author = {Kang*, Hyeonsu B. and Mysore*, Sheshera and Huang*, Kevin and Chang, Haw-Shiuan and Prein, Thorben and McCallum, Andrew and Kittur, Aniket and Olivetti, Elsa},
     booktitle = {Bridging Human-Computer Interaction and Natural Language Processing (HCI+NLP)},
     year = {2022},
     paper = {https://arxiv.org/abs/2206.01328}
   }

2021

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

   Paper Talk Bib Code Poster Slides

   @inproceedings{chang2021changing,
     title = {Changing the Mind of Transformers for Topically-Controllable Language Generation},
     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},
   }

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

   Paper Talk Bib Code Poster Slides

   @inproceedings{chang2021multi-facet,
     title = {Multi-facet Universal Schema},
     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},
   }

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

   Paper Bib Poster Slides

   @inproceedings{chang2021extending,
     title = {Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications},
     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},
   }

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

   Paper Bib

   @inproceedings{Seoh_EMNLP_21,
     title = {Open Aspect Target Sentiment Classification with Natural Language Prompts},
     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

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

   Paper Talk Bib Slides

   @article{chang2019ovecoming,
     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},
   }

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, and 12 more authors

   In KDD ’20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020, 2020

   Paper Bib

   @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},
     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}
   }

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 1 more author

   J. Chem. Inf. Model., 2020

   Paper Bib

   @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},
     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

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

   Paper Bib

   @inproceedings{mysore2019msannlaw,
     title = {The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures},
     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

1. TMM

   Active Learning for Crowdsourced QoE Modeling

   Haw-Shiuan Chang, Chih-Fan Hsu, Tobias Hoßfeld, and Kuan-Ta Chen

   IEEE Trans. Multim., 2018

   Paper Bib

   @article{DBLP:journals/tmm/ChangHHC18,
     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}
   }

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

   Paper Bib Code Poster

   @inproceedings{chang2017unsupervised,
     title = {Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection},
     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},
   }

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

   Paper Bib Slides

   @inproceedings{conf/TextGraph18/Chang18,
     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},
     paper = {https://arxiv.org/abs/1804.03257}
   }

2017

1. NeurIPS

   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 (NeurIPS), 2017

   Paper Bib Poster

   @inproceedings{DBLP:conf/nips/ChangLM17,
     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 (NeurIPS)},
     year = {2017},
     paper = {http://arxiv.org/abs/1704.07433}
   }

2. NeurIPS 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

   Paper Bib

   @inproceedings{mysore2017automatically,
     title = {Automatically Extracting Action Graphs from Materials Science Synthesis Procedures},
     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

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

   Paper Bib

   @inproceedings{DBLP:conf/tac/Chang16,
     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

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

   Paper Demo Dataset Bib Code Slides

   @inproceedings{DBLP:conf/edm/ChangHC15,
     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},
     dataset = {https://pslcdatashop.web.cmu.edu/DatasetInfo?datasetId=1198}
   }

2. CVIU

   Optimizing the Decomposition for Multiple Foreground Cosegmentation

   Haw-Shiuan Chang, and Yu-Chiang Frank Wang

   Computer Vision and Image Understanding (CVIU), 2015

   Paper Bib

   @article{CHANG201518,
     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},
     paper = {proj11-cv-Decomposition of Multiple Foreground Co-segmentation-paper.pdf}
   }

2014

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

   Paper Bib Poster

   @inproceedings{DBLP:conf/accv/ChangW14,
     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},
     paper = {proj10-cv-Hierarchical Image Segmentation without Training-paper.pdf}
   }

2013

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

   Paper Bib Poster

   @inproceedings{DBLP:conf/icip/ChangW13,
     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},
     paper = {proj12-cv-Superpixel-Based Large Displacement Optical Flow-paper.pdf}
   }

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

   Paper Bib

   @article{6482623,
     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}
   }