Haw-Shiuan Chang

According to our database, Haw-Shiuan Chang authored at least 34 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Vivek Subramanian, Tagyoung Chung, Mohit Bansal, Nanyun Peng

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 via Asymptotic Entropy.

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

CoRR, 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

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 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, Vivek Subramanian, Tagyoung Chung, Mohit Bansal, Nanyun Peng

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

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

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

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Encoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens.

Ronald Seoh, Haw-Shiuan Chang, Andrew McCallum

CoRR, 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, Andrew McCallum

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling.

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

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Augmenting Scientific Creativity with Retrieval across Knowledge Domains.

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

CoRR, 2022

Unsupervised Partial Sentence Matching for Cited Text Identification.

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

Proceedings of the Third Workshop on Scholarly Document Processing, 2022

Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions.

Haw-Shiuan Chang, Andrew McCallum

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Open Aspect Target Sentiment Classification with Natural Language Prompts.

Ronald Seoh, Ian Birle, Mrinal Tak, Haw-Shiuan Chang, Brian Pinette, Alfred Hough

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Multi-facet Universal Schema.

Rohan Paul, Haw-Shiuan Chang, Andrew McCallum

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Changing the Mind of Transformers for Topically-Controllable Language Generation.

Haw-Shiuan Chang, Jiaming Yuan, Mohit Iyyer, Andrew McCallum

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications.

Haw-Shiuan Chang, Amol Agrawal, Andrew McCallum

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

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

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks.

Edward Kim, Zach Jensen, Alexander van Grootel, Kevin Huang, Matthew Staib, Sheshera Mysore, Haw-Shiuan Chang, Emma Strubell, Andrew McCallum, Stefanie Jegelka, Elsa Olivetti

J. Chem. Inf. Model., 2020

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, Jiawei Han

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

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

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, Elsa Olivetti

Proceedings of the 13th Linguistic Annotation Workshop, 2019

2018

Active Learning for Crowdsourced QoE Modeling.

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

IEEE Trans. Multim., 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

Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing, 2018

Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection.

Haw-Shiuan Chang, ZiYun Wang, Luke Vilnis, Andrew McCallum

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

2017

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, Elsa Olivetti

CoRR, 2017

Unsupervised Hypernym Detection by Distributional Inclusion Vector Embedding.

Haw-Shiuan Chang, ZiYun Wang, Luke Vilnis, Andrew McCallum

CoRR, 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

Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples.

Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

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, Andrew McCallum

Proceedings of the 2016 Text Analysis Conference, 2016

2015

Optimizing the decomposition for multiple foreground cosegmentation.

Haw-Shiuan Chang, Yu-Chiang Frank Wang

Comput. Vis. Image Underst., 2015

Modeling Exercise Relationships in E-Learning: A Unified Approach.

Haw-Shiuan Chang, Hwai-Jung Hsu, Kuan-Ta Chen

Proceedings of the 8th International Conference on Educational Data Mining, 2015

2014

Simple-to-Complex Discriminative Clustering for Hierarchical Image Segmentation.

Haw-Shiuan Chang, Yu-Chiang Frank Wang

Proceedings of the Computer Vision - ACCV 2014, 2014

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

Superpixel-based large displacement optical flow.

Haw-Shiuan Chang, Yu-Chiang Frank Wang

Proceedings of the IEEE International Conference on Image Processing, 2013