Superpixel-based large displacement optical flow. - Haw-Shiuan Chang; Yu-Chiang Frank Wang (ICIP, 2013)

Exploring Visual and Motion Saliency for Automatic Video Object Extraction. - Wei-Te Li; Haw-Shiuan Chang; Kuo-Chin Lien; Hui-Tang Chang; Yu-Chiang Frank Wang (IEEE Trans. Image Process., 2013)

Simple-to-Complex Discriminative Clustering for Hierarchical Image Segmentation. - Haw-Shiuan Chang; Yu-Chiang Frank Wang (ACCV (3), 2014)

Modeling Exercise Relationships in E-Learning: A Unified Approach. - Haw-Shiuan Chang; Hwai-Jung Hsu; Kuan-Ta Chen (EDM, 2015)

Optimizing the decomposition for multiple foreground cosegmentation. - Haw-Shiuan Chang; Yu-Chiang Frank Wang (Comput. Vis. Image Underst., 2015)

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 003; Johnny Tian-Zheng Wei; Aaron Traylor; Ajay Nagesh; Nicholas Monath; Patrick Verga; Emma Strubell; Andrew McCallum (TAC, 2016)

Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples. - Haw-Shiuan Chang; Erik G. Learned-Miller; Andrew McCallum (NIPS, 2017)

Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples. - Haw-Shiuan Chang; Erik G. Learned-Miller; Andrew McCallum (CoRR, 2017)

Unsupervised Hypernym Detection by Distributional Inclusion Vector Embedding. - Haw-Shiuan Chang; ZiYun Wang; Luke Vilnis; Andrew McCallum (CoRR, 2017)

Automatically Extracting Action Graphs from Materials Science Synthesis Procedures. - Sheshera Mysore; Edward Kim 004; Emma Strubell; Ao Liu 003; Haw-Shiuan Chang; Srikrishna Kompella; Kevin Huang 004; Andrew McCallum; Elsa A. Olivetti (CoRR, 2017)

Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection. - Haw-Shiuan Chang; ZiYun Wang; Luke Vilnis; Andrew McCallum (NAACL-HLT, 2018)

Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings. - Haw-Shiuan Chang; Amol Agrawal; Ananya Ganesh; Anirudha Desai; Vinayak Mathur; Alfred Hough; Andrew McCallum (TextGraphs@NAACL-HLT, 2018)

Active Learning for Crowdsourced QoE Modeling. - Haw-Shiuan Chang; Chih-Fan Hsu; Tobias Hoßfeld; Kuan-Ta Chen (IEEE Trans. Multim., 2018)

The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures. - Sheshera Mysore; Zach Jensen; Edward Kim 004; Kevin Huang 004; Haw-Shiuan Chang; Emma Strubell; Jeffrey Flanigan; Andrew McCallum; Elsa A. Olivetti (LAW@ACL, 2019)

Overcoming Practical Issues of Deep Active Learning and its Applications on Named Entity Recognition. - Haw-Shiuan Chang; Shankar Vembu; Sunil Mohan; Rheeya Uppaal; Andrew McCallum (CoRR, 2019)

AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types. - Xin Luna Dong; Xiang He 007; Andrey Kan; Xian Li; Yan Liang 004; Jun Ma 029; Yifan Ethan Xu; Chenwei Zhang; Tong Zhao 002; Gabriel Blanco Saldana; Saurabh Deshpande; Alexandre Michetti Manduca; et al. (KDD, 2020)

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks. - Edward Kim 004; Zach Jensen; Alexander van Grootel; Kevin Huang 004; Matthew Staib; Sheshera Mysore; Haw-Shiuan Chang; Emma Strubell; Andrew McCallum; Stefanie Jegelka; Elsa A. Olivetti (J. Chem. Inf. Model., 2020)

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; Andrew McCallum (Mach. Learn., 2020)

Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications. - Haw-Shiuan Chang; Amol Agrawal; Andrew McCallum (AAAI, 2021)

Changing the Mind of Transformers for Topically-Controllable Language Generation. - Haw-Shiuan Chang; Jiaming Yuan; Mohit Iyyer; Andrew McCallum (EACL, 2021)

Multi-facet Universal Schema. - Rohan Paul; Haw-Shiuan Chang; Andrew McCallum (EACL, 2021)

Open Aspect Target Sentiment Classification with Natural Language Prompts. - Ronald Seoh; Ian Birle; Mrinal Tak; Haw-Shiuan Chang; Brian Pinette; Alfred Hough (EMNLP (1), 2021)

Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions. - Haw-Shiuan Chang; Andrew McCallum (ACL (1), 2022)

Unsupervised Partial Sentence Matching for Cited Text Identification. - Kathryn Ricci; Haw-Shiuan Chang; Purujit Goyal; Andrew McCallum (SDP@COLING, 2022)

Augmenting Scientific Creativity with Retrieval across Knowledge Domains. - Hyeonsu B. Kang; Sheshera Mysore; Kevin Huang 004; Haw-Shiuan Chang; Thorben Prein; Andrew McCallum; Aniket Kittur; Elsa A. Olivetti (CoRR, 2022)

Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling. - Haw-Shiuan Chang; Ruei-Yao Sun; Kathryn Ricci; Andrew McCallum (ACL (1), 2023)

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 001; Andrew McCallum (ACL (Findings), 2023)

Encoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens. - Ronald Seoh; Haw-Shiuan Chang; Andrew McCallum (CoRR, 2023)

Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM. - Haw-Shiuan Chang; Nanyun Peng 001; Mohit Bansal; Anil Ramakrishna; Tagyoung Chung (EMNLP, 2024)

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 007; Vivek Subramanian; Tagyoung Chung; Mohit Bansal; Nanyun Peng 001 (EMNLP (Findings), 2024)

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; Andrew McCallum (WSDM, 2024)

REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation via Asymptotic Entropy. - Haw-Shiuan Chang; Nanyun Peng 001; Mohit Bansal; Anil Ramakrishna; Tagyoung Chung (CoRR, 2024)

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; Haw-Shiuan Chang (CoRR, 2024)

REAL Sampling: Boosting Factuality and Diversity of Open-ended Generation by Extrapolating the Entropy of an Infinitely Large LM. - Haw-Shiuan Chang; Nanyun Peng 001; Mohit Bansal; Anil Ramakrishna; Tagyoung Chung (Trans. Assoc. Comput. Linguistics, 2025)

CoKe: Customizable Fine-Grained Story Evaluation via Chain-of-Keyword Rationalization. - Brihi Joshi; Sriram Venkatapathy; Mohit Bansal; Nanyun Peng 001; Haw-Shiuan Chang (CoRR, 2025)