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ORCIDHal Daumé III
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- affiliation: University of Maryland, College Park, MD, USA
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2020 – today
- 2023
[c157]Arjun Subramonian, Xingdi Yuan, Hal Daumé III, Su Lin Blodgett:
It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance. ACL (Findings) 2023: 3234-3279- [c156]Lingjun Zhao, Khanh Nguyen, Hal Daumé III:
Define, Evaluate, and Improve Task-Oriented Cognitive Capabilities for Instruction Generation Models. ACL (Findings) 2023: 3688-3706 - [c155]Eve Fleisig, Aubrie Amstutz, Chad Atalla, Su Lin Blodgett, Hal Daumé III, Alexandra Olteanu, Emily Sheng, Dan Vann, Hanna M. Wallach:
FairPrism: Evaluating Fairness-Related Harms in Text Generation. ACL (1) 2023: 6231-6251 - [c154]Navita Goyal, Ani Nenkova, Hal Daumé III:
Factual or Contextual? Disentangling Error Types in Entity Description Generation. ACL (1) 2023: 8322-8340 - [c153]Connor Baumler, Anna Sotnikova, Hal Daumé III:
Which Examples Should be Multiply Annotated? Active Learning When Annotators May Disagree. ACL (Findings) 2023: 10352-10371 - [c152]Upol Ehsan
, Philipp Wintersberger, Elizabeth Anne Watkins, Carina Manger, Gonzalo Ramos, Justin D. Weisz, Hal Daumé III, Andreas Riener, Mark O. Riedl:
Human-Centered Explainable AI (HCXAI): Coming of Age. CHI Extended Abstracts 2023: 353:1-353:7 - [i81]Lingjun Zhao, Khanh Nguyen, Hal Daumé III:
A Cognitive Evaluation of Instruction Generation Agents tl;dr They Need Better Theory-of-Mind Capabilities. CoRR abs/2301.05149 (2023) - [i80]Aashaka Desai, Lauren Berger, Fyodor O. Minakov, Vanessa Milan, Chinmay Singh, Kriston Pumphrey, Richard E. Ladner, Hal Daumé III, Alex X. Lu, Naomi Caselli, Danielle Bragg:
ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition. CoRR abs/2304.05934 (2023) - [i79]Arjun Subramonian, Xingdi Yuan, Hal Daumé III, Su Lin Blodgett:
It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance. CoRR abs/2305.09022 (2023) - [i78]Navita Goyal, Eleftheria Briakou, Amanda Liu, Connor Baumler, Claire Bonial, Jeffrey Micher, Clare R. Voss, Marine Carpuat, Hal Daumé III:
What Else Do I Need to Know? The Effect of Background Information on Users' Reliance on AI Systems. CoRR abs/2305.14331 (2023) - [i77]Irene Solaiman, Zeerak Talat, William Agnew, Lama Ahmad, Dylan K. Baker, Su Lin Blodgett, Hal Daumé III, Jesse Dodge, Ellie Evans, Sara Hooker, Yacine Jernite, Alexandra Sasha Luccioni, Alberto Lusoli, Margaret Mitchell, Jessica Newman, Marie-Therese Png, Andrew Strait, Apostol Vassilev:
Evaluating the Social Impact of Generative AI Systems in Systems and Society. CoRR abs/2306.05949 (2023) - [i76]Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao, Huazhe Xu, Hal Daumé III, Furong Huang:
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning. CoRR abs/2306.13229 (2023) - 2022
- [j23]Matthew Marge, Carol Y. Espy-Wilson, Nigel G. Ward, Abeer Alwan, Yoav Artzi, Mohit Bansal, Gilmer L. Blankenship, Joyce Chai, Hal Daumé III, Debadeepta Dey, Mary P. Harper, Thomas Howard, Casey Kennington, Ivana Kruijff-Korbayová, Dinesh Manocha, Cynthia Matuszek, Ross Mead, Raymond J. Mooney, Roger K. Moore, Mari Ostendorf, Heather Pon-Barry, Alexander I. Rudnicky, Matthias Scheutz, Robert St. Amant, Tong Sun, Stefanie Tellex, David R. Traum, Zhou Yu:
Spoken language interaction with robots: Recommendations for future research. Comput. Speech Lang. 71: 101255 (2022) - [j22]Dhanya Sridhar, Hal Daumé III, David M. Blei:
Heterogeneous Supervised Topic Models. Trans. Assoc. Comput. Linguistics 10: 732-745 (2022) - [c151]Upol Ehsan, Philipp Wintersberger, Q. Vera Liao, Elizabeth Anne Watkins, Carina Manger, Hal Daumé III, Andreas Riener, Mark O. Riedl:
Human-Centered Explainable AI (HCXAI): Beyond Opening the Black-Box of AI. CHI Extended Abstracts 2022: 109:1-109:7 - [c150]Amr Sharaf, Hal Daumé III, Renkun Ni:
Promoting Fairness in Learned Models by Learning to Active Learn under Parity Constraints. FAccT 2022: 2149-2156 - [c149]Khanh X. Nguyen, Yonatan Bisk, Hal Daumé III:
A Framework for Learning to Request Rich and Contextually Useful Information from Humans. ICML 2022: 16553-16568 - [c148]Yang Trista Cao, Kyle Seelman, Kyungjun Lee, Hal Daumé III:
What's Different between Visual Question Answering for Machine "Understanding" Versus for Accessibility? AACL/IJCNLP (1) 2022: 1025-1034 - [c147]Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler, Hal Daumé III, Kaheer Suleman, Alexandra Olteanu:
Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications. NAACL-HLT 2022: 314-324 - [c146]Yang Trista Cao, Anna Sotnikova, Hal Daumé III, Rachel Rudinger, Linda Zou:
Theory-Grounded Measurement of U.S. Social Stereotypes in English Language Models. NAACL-HLT 2022: 1276-1295 - [i75]Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler, Hal Daumé III, Kaheer Suleman, Alexandra Olteanu:
Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications. CoRR abs/2205.06828 (2022) - [i74]Yang Trista Cao, Anna Sotnikova, Hal Daumé III, Rachel Rudinger, Linda Zou:
Theory-Grounded Measurement of U.S. Social Stereotypes in English Language Models. CoRR abs/2206.11684 (2022) - [i73]Yang Trista Cao, Kyle Seelman, Kyungjun Lee, Hal Daumé III:
What's Different between Visual Question Answering for Machine "Understanding" Versus for Accessibility? CoRR abs/2210.14966 (2022) - [i72]Upol Ehsan, Q. Vera Liao, Samir Passi, Mark O. Riedl, Hal Daumé III:
Seamful XAI: Operationalizing Seamful Design in Explainable AI. CoRR abs/2211.06753 (2022) - [i71]Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé III, Emma Pierson, Nihar B. Shah:
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions? CoRR abs/2211.12966 (2022) - 2021
- [j21]Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miroslav Dudík, Benjamin Fish, Mary L. Gray, Brent J. Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach, Marion Zepf:
Responsible computing during COVID-19 and beyond. Commun. ACM 64(7): 30-32 (2021) - [j20]Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford:
Datasheets for datasets. Commun. ACM 64(12): 86-92 (2021) - [j19]Yang Trista Cao, Hal Daumé III:
Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning Lifecycle. Comput. Linguistics 47(3): 615-661 (2021) - [j18]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. Proc. ACM Hum. Comput. Interact. 5(CSCW1): 75:1-75:17 (2021) - [c145]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. AAAI 2021: 4785-4793 - [c144]Amr Sharaf, Hal Daumé III:
Meta-Learning Effective Exploration Strategies for Contextual Bandits. AAAI 2021: 9541-9548 - [c143]Anna Sotnikova, Yang Trista Cao, Hal Daumé III, Rachel Rudinger:
Analyzing Stereotypes in Generative Text Inference Tasks. ACL/IJCNLP (Findings) 2021: 4052-4065 - [c142]Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III:
Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation. EMNLP (1) 2021: 9612-9622 - [c141]David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan:
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. HCOMP 2021: 35-47 - [c140]Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III:
Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval. NAACL-HLT 2021: 4635-4641 - [i70]Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III:
Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval. CoRR abs/2104.05883 (2021) - [i69]David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan:
A Human-Centered Interpretability Framework Based on Weight of Evidence. CoRR abs/2104.13299 (2021) - [i68]Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III:
Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence Annotation. CoRR abs/2110.04889 (2021) - [i67]Khanh Nguyen, Yonatan Bisk, Hal Daumé III:
Learning When and What to Ask: a Hierarchical Reinforcement Learning Framework. CoRR abs/2110.08258 (2021) - 2020
- [j17]Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daumé III, Lise Getoor:
Interpretable Engagement Models for MOOCs Using Hinge-Loss Markov Random Fields. IEEE Trans. Learn. Technol. 13(1): 107-122 (2020) - [c139]Kianté Brantley, Hal Daumé III, Amr Sharaf:
Active Imitation Learning with Noisy Guidance. ACL 2020: 2093-2105 - [c138]Yang Trista Cao, Hal Daumé III:
Toward Gender-Inclusive Coreference Resolution. ACL 2020: 4568-4595 - [c137]Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach:
Language (Technology) is Power: A Critical Survey of "Bias" in NLP. ACL 2020: 5454-5476 - [c136]Amr Sharaf, Hany Hassan, Hal Daumé III:
Meta-Learning for Few-Shot NMT Adaptation. NGT@ACL 2020: 43-53 - [c135]Tianze Shi, Chen Zhao, Jordan L. Boyd-Graber, Hal Daumé III, Lillian Lee:
On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries. EMNLP (Findings) 2020: 1849-1864 - [c134]Abigail Z. Jacobs, Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach:
The meaning and measurement of bias: lessons from natural language processing. FAT* 2020: 706 - [c133]Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck:
Operationalizing the Legal Principle of Data Minimization for Personalization. SIGIR 2020: 399-408 - [i66]Amr Sharaf, Hany Hassan, Hal Daumé III:
Meta-Learning for Few-Shot NMT Adaptation. CoRR abs/2004.02745 (2020) - [i65]Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma, Abhyuday Jagannatha, David W. Jacobs, Hal Daumé III:
Towards Automatic Generation of Questions from Long Answers. CoRR abs/2004.05109 (2020) - [i64]Kianté Brantley, Amr Sharaf, Hal Daumé III:
Active Imitation Learning with Noisy Guidance. CoRR abs/2005.12801 (2020) - [i63]Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck:
Operationalizing the Legal Principle of Data Minimization for Personalization. CoRR abs/2005.13718 (2020) - [i62]Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach:
Language (Technology) is Power: A Critical Survey of "Bias" in NLP. CoRR abs/2005.14050 (2020) - [i61]Khanh Nguyen, Hal Daumé III:
Active Imitation Learning from Multiple Non-Deterministic Teachers: Formulation, Challenges, and Algorithms. CoRR abs/2006.07777 (2020) - [i60]Tianze Shi, Chen Zhao, Jordan L. Boyd-Graber, Hal Daumé III, Lillian Lee:
On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries. CoRR abs/2010.11246 (2020) - [i59]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. CoRR abs/2011.14646 (2020) - [i58]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. CoRR abs/2011.15050 (2020) - [i57]Ivan Stelmakh, Charvi Rastogi, Nihar B. Shah, Aarti Singh, Hal Daumé III:
A Large Scale Randomized Controlled Trial on Herding in Peer-Review Discussions. CoRR abs/2011.15083 (2020)
2010 – 2019
- 2019
- [j16]Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, Hal Daumé III, John Langford:
Active Learning for Cost-Sensitive Classification. J. Mach. Learn. Res. 20: 65:1-65:50 (2019) - [c132]Yang Trista Cao, Sudha Rao, Hal Daumé III:
Controlling the Specificity of Clarification Question Generation. WNLP@ACL 2019: 53-56 - [c131]Kianté Brantley, Kyunghyun Cho, Hal Daumé III, Sean Welleck:
Non-Monotonic Sequential Text Generation. WNLP@ACL 2019: 57-59 - [c130]Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach:
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? CHI 2019: 600 - [c129]Khanh Nguyen, Hal Daumé III:
Help, Anna! Visual Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning. EMNLP/IJCNLP (1) 2019: 684-695 - [c128]Elissa M. Redmiles, Lisa N. Maszkiewicz, Emily Hwang, Dhruv Kuchhal, Everest Liu, Miraida Morales, Denis Peskov, Sudha Rao, Rock Stevens, Kristina Gligoric, Sean Kross, Michelle L. Mazurek, Hal Daumé III:
Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts. EMNLP/IJCNLP (1) 2019: 4830-4841 - [c127]Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro:
Contextual Memory Trees. ICML 2019: 6026-6035 - [c126]Sean Welleck, Kianté Brantley, Hal Daumé III, Kyunghyun Cho:
Non-Monotonic Sequential Text Generation. ICML 2019: 6716-6726 - [c125]Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand Negahban:
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback. ICML 2019: 7335-7344 - [c124]Sudha Rao, Hal Daumé III:
Answer-based Adversarial Training for Generating Clarification Questions. NAACL-HLT (1) 2019: 143-155 - [c123]Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire:
Reinforcement Learning with Convex Constraints. NeurIPS 2019: 14070-14079 - [i56]Khanh Nguyen, Hal Daumé III:
Help, Anna! Visual Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning. ViGIL@NeurIPS 2019 - [i55]Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand N. Negahban:
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback. CoRR abs/1901.00301 (2019) - [i54]Amr Sharaf, Hal Daumé III:
Meta-Learning for Contextual Bandit Exploration. CoRR abs/1901.08159 (2019) - [i53]Sean Welleck, Kianté Brantley, Hal Daumé III, Kyunghyun Cho:
Non-Monotonic Sequential Text Generation. CoRR abs/1902.02192 (2019) - [i52]Sudha Rao, Hal Daumé III:
Answer-based Adversarial Training for Generating Clarification Questions. CoRR abs/1904.02281 (2019) - [i51]Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire:
Reinforcement Learning with Convex Constraints. CoRR abs/1906.09323 (2019) - [i50]Khanh Nguyen, Hal Daumé III:
Help, Anna! Visual Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning. CoRR abs/1909.01871 (2019) - [i49]Khanh Nguyen, Hal Daumé III:
Global Voices: Crossing Borders in Automatic News Summarization. CoRR abs/1910.00421 (2019) - [i48]David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna M. Wallach:
Weight of Evidence as a Basis for Human-Oriented Explanations. CoRR abs/1910.13503 (2019) - [i47]Yang Trista Cao, Hal Daumé III:
Toward Gender-Inclusive Coreference Resolution. CoRR abs/1910.13913 (2019) - 2018
- [c122]Sudha Rao, Hal Daumé III:
Learning to Ask Good Questions: Ranking Clarification Questions using Neural Expected Value of Perfect Information. ACL (1) 2018: 2737-2746 - [c121]Han-Chin Shing, Suraj Nair, Ayah Zirikly, Meir Friedenberg, Hal Daumé III, Philip Resnik:
Expert, Crowdsourced, and Machine Assessment of Suicide Risk via Online Postings. CLPsych@NAACL-HTL 2018: 25-36 - [c120]Chris Kedzie, Kathleen R. McKeown, Hal Daumé III:
Content Selection in Deep Learning Models of Summarization. EMNLP 2018: 1818-1828 - [c119]Hal Daumé III, John Langford, Amr Sharaf:
Residual Loss Prediction: Reinforcement Learning With No Incremental Feedback. ICLR (Poster) 2018 - [c118]Hoang Minh Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III:
Hierarchical Imitation and Reinforcement Learning. ICML 2018: 2923-2932 - [c117]Octavian Suciu, Radu Marginean, Yigitcan Kaya, Hal Daumé III, Tudor Dumitras:
When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks. USENIX Security Symposium 2018: 1299-1316 - [i46]Hoang Minh Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III:
Hierarchical Imitation and Reinforcement Learning. CoRR abs/1803.00590 (2018) - [i45]Octavian Suciu, Radu Marginean, Yigitcan Kaya, Hal Daumé III, Tudor Dumitras:
When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks. CoRR abs/1803.06975 (2018) - [i44]Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford:
Datasheets for Datasets. CoRR abs/1803.09010 (2018) - [i43]Sudha Rao, Hal Daumé III:
Learning to Ask Good Questions: Ranking Clarification Questions using Neural Expected Value of Perfect Information. CoRR abs/1805.04655 (2018) - [i42]Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro:
Contextual Memory Trees. CoRR abs/1807.06473 (2018) - [i41]Chris Kedzie, Kathleen R. McKeown, Hal Daumé III:
Content Selection in Deep Learning Models of Summarization. CoRR abs/1810.12343 (2018) - [i40]Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach:
Improving fairness in machine learning systems: What do industry practitioners need? CoRR abs/1812.05239 (2018) - 2017
- [c116]Snigdha Chaturvedi, Mohit Iyyer, Hal Daumé III:
Unsupervised Learning of Evolving Relationships Between Literary Characters. AAAI 2017: 3159-3165 - [c115]Sudha Rao, Daniel Marcu, Kevin Knight, Hal Daumé III:
Biomedical Event Extraction using Abstract Meaning Representation. BioNLP 2017: 126-135 - [c114]Mohit Iyyer, Varun Manjunatha, Anupam Guha, Yogarshi Vyas, Jordan L. Boyd-Graber, Hal Daumé III, Larry S. Davis:
The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives. CVPR 2017: 6478-6487 - [c113]Amr Sharaf, Hal Daumé III:
Structured Prediction via Learning to Search under Bandit Feedback. SPNLP@EMNLP 2017: 17-26 - [c112]Khanh Nguyen, Hal Daumé III, Jordan L. Boyd-Graber:
Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback. EMNLP 2017: 1464-1474 - [c111]Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro:
Logarithmic Time One-Against-Some. ICML 2017: 923-932 - [c110]Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, Hal Daumé III, John Langford:
Active Learning for Cost-Sensitive Classification. ICML 2017: 1915-1924 - [c109]Amr Sharaf, Shi Feng, Khanh Nguyen, Kianté Brantley, Hal Daumé III:
The UMD Neural Machine Translation Systems at WMT17 Bandit Learning Task. WMT 2017: 667-673 - [i39]Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, Hal Daumé III, John Langford:
Active Learning for Cost-Sensitive Classification. CoRR abs/1703.01014 (2017) - [i38]Khanh Nguyen, Hal Daumé III, Jordan L. Boyd-Graber:
Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback. CoRR abs/1707.07402 (2017) - [i37]Amr Sharaf, Shi Feng, Khanh Nguyen, Kianté Brantley, Hal Daumé III:
The UMD Neural Machine Translation Systems at WMT17 Bandit Learning Task. CoRR abs/1708.01318 (2017) - [i36]Allyson Ettinger, Sudha Rao, Hal Daumé III, Emily M. Bender:
Towards Linguistically Generalizable NLP Systems: A Workshop and Shared Task. CoRR abs/1711.01505 (2017) - 2016
- [j15]Vicente Ordonez, Xufeng Han, Polina Kuznetsova, Girish Kulkarni, Margaret Mitchell, Kota Yamaguchi, Karl Stratos, Amit Goyal, Jesse Dodge, Alyssa C. Mensch, Hal Daumé III, Alexander C. Berg, Yejin Choi, Tamara L. Berg:
Large Scale Retrieval and Generation of Image Descriptions. Int. J. Comput. Vis. 119(1): 46-59 (2016) - [j14]Kathy McKeown, Hal Daumé III, Snigdha Chaturvedi, John Paparrizos, Kapil Thadani, Pablo Barrio, Or Biran, Suvarna Bothe, Michael Collins, Kenneth R. Fleischmann, Luis Gravano, Rahul Jha, Ben King, Kevin McInerney, Taesun Moon, Arvind Neelakantan, Diarmuid Ó Séaghdha, Dragomir R. Radev, Thomas Clay Templeton, Simone Teufel:
Predicting the impact of scientific concepts using full-text features. J. Assoc. Inf. Sci. Technol. 67(11): 2684-2696 (2016) - [j13]Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro:
Learning Reductions That Really Work. Proc. IEEE 104(1): 136-147 (2016) - [c108]Hadi Amiri, Hal Daumé III:
Short Text Representation for Detecting Churn in Microblogs. AAAI 2016: 2566-2572 - [c107]Snigdha Chaturvedi, Dan Goldwasser, Hal Daumé III:
Ask, and Shall You Receive? Understanding Desire Fulfillment in Natural Language Text. AAAI 2016: 2697-2703 - [c106]Snigdha Chaturvedi, Shashank Srivastava, Hal Daumé III, Chris Dyer:
Modeling Evolving Relationships Between Characters in Literary Novels. AAAI 2016: 2704-2710 - [c105]Hadi Amiri, Philip Resnik, Jordan L. Boyd-Graber, Hal Daumé III:
Learning Text Pair Similarity with Context-sensitive Autoencoders. ACL (1) 2016 - [c104]Meir Friedenberg, Hadi Amiri, Hal Daumé III, Philip Resnik:
The UMD CLPsych 2016 Shared Task System: Text Representation for Predicting Triage of Forum Posts about Mental Health. CLPsych@HLT-NAACL 2016: 158-161 - [c103]He He, Jordan L. Boyd-Graber, Hal Daumé III:
Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation. HLT-NAACL 2016: 971-976 - [c102]Mohit Iyyer, Anupam Guha, Snigdha Chaturvedi, Jordan L. Boyd-Graber, Hal Daumé III:
Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships. HLT-NAACL 2016: 1534-1544 - [c101]Kai-Wei Chang, He He, Stéphane Ross, Hal Daumé III, John Langford:
A Credit Assignment Compiler for Joint Prediction. NIPS 2016: 1705-1713 - [c100]Sudha Rao, Yogarshi Vyas, Hal Daumé III, Philip Resnik:
CLIP$@$UMD at SemEval-2016 Task 8: Parser for Abstract Meaning Representation using Learning to Search. SemEval@NAACL-HLT 2016: 1190-1196 - [c99]Fabienne Braune, Alexander M. Fraser, Hal Daumé III, Ales Tamchyna:
A Framework for Discriminative Rule Selection in Hierarchical Moses. WMT 2016: 92-101 - [i35]Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro:
Logarithmic Time One-Against-Some. CoRR abs/1606.04988 (2016) - [i34]