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2020 – today
- 2024
[c80]Younghun Lee, Dan Goldwasser, Laura Schwab Reese:
Towards Understanding Counseling Conversations: Domain Knowledge and Large Language Models. EACL (Findings) 2024: 2032-2047- [c79]Nikhil Mehta, Dan Goldwasser:
An Interactive Framework for Profiling News Media Sources. NAACL-HLT 2024: 40-58 - [c78]Maryam Davoodi, Dan Goldwasser:
Analysis of State-Level Legislative Process in Enhanced Linguistic and Nationwide Network Contexts. NAACL-HLT 2024: 7404-7422 - [i38]Younghun Lee, Dan Goldwasser, Laura Schwab Reese:
Towards Understanding Counseling Conversations: Domain Knowledge and Large Language Models. CoRR abs/2402.14200 (2024) - [i37]Tunazzina Islam, Dan Goldwasser:
Uncovering Latent Themes of Messaging on Social Media by Integrating LLMs: A Case Study on Climate Campaigns. CoRR abs/2403.10707 (2024) - [i36]Tunazzina Islam, Dan Goldwasser:
Uncovering Latent Arguments in Social Media Messaging by Employing LLMs-in-the-Loop Strategy. CoRR abs/2404.10259 (2024) - [i35]Nikhil Mehta, Dan Goldwasser:
Using RL to Identify Divisive Perspectives Improves LLMs Abilities to Identify Communities on Social Media. CoRR abs/2406.00969 (2024) - 2023
- [c77]Maria Leonor Pacheco
, Tunazzina Islam, Lyle H. Ungar, Ming Yin, Dan Goldwasser:
Interactive Concept Learning for Uncovering Latent Themes in Large Text Collections. ACL (Findings) 2023: 5059-5080 - [c76]Tunazzina Islam, Ruqi Zhang, Dan Goldwasser:
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging. AIES 2023: 15-25 - [c75]Nishanth Sridhar Nakshatri, Siyi Liu, Sihao Chen, Dan Roth, Dan Goldwasser, Daniel Hopkins:
Using LLM for Improving Key Event Discovery: Temporal-Guided News Stream Clustering with Event Summaries. EMNLP (Findings) 2023: 4162-4173 - [c74]Shamik Roy, Dan Goldwasser:
"A Tale of Two Movements': Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Prediction. EMNLP (Findings) 2023: 10437-10467 - [c73]Nan Jiang, Thibaud Lutellier, Yiling Lou, Lin Tan, Dan Goldwasser, Xiangyu Zhang:
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair. ICSE 2023: 1251-1263 - [c72]Tunazzina Islam, Shamik Roy, Dan Goldwasser:
Weakly Supervised Learning for Analyzing Political Campaigns on Facebook. ICWSM 2023: 411-422 - [c71]Nikhil Mehta, Dan Goldwasser:
Interactively Learning Social Media Representations Improves News Source Factuality Detection. IJCNLP (Findings) 2023: 291-311 - [i34]Nan Jiang, Thibaud Lutellier, Yiling Lou, Lin Tan, Dan Goldwasser, Xiangyu Zhang:
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair. CoRR abs/2302.01857 (2023) - [i33]Shamik Roy, Nishanth Sridhar Nakshatri, Dan Goldwasser:
Towards Few-Shot Identification of Morality Frames using In-Context Learning. CoRR abs/2302.02029 (2023) - [i32]Maria Leonor Pacheco, Tunazzina Islam, Lyle H. Ungar, Ming Yin, Dan Goldwasser:
Interactive Concept Learning for Uncovering Latent Themes in Large Text Collections. CoRR abs/2305.05094 (2023) - [i31]Tunazzina Islam, Ruqi Zhang, Dan Goldwasser:
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging. CoRR abs/2305.06174 (2023) - [i30]Nikhil Mehta, Dan Goldwasser:
An Interactive Framework for Profiling News Media Sources. CoRR abs/2309.07384 (2023) - [i29]Nikhil Mehta, Dan Goldwasser:
Interactively Learning Social Media Representations Improves News Source Factuality Detection. CoRR abs/2309.14966 (2023) - [i28]Shamik Roy, Dan Goldwasser:
"A Tale of Two Movements": Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Prediction. CoRR abs/2310.07155 (2023) - [i27]Rajkumar Pujari, Chengfei Wu, Dan Goldwasser:
"We Demand Justice!": Towards Grounding Political Text in Social Context. CoRR abs/2311.09106 (2023) - 2022
- [c70]Maryam Davoodi, Eric Waltenburg, Dan Goldwasser:
Modeling U.S. State-Level Policies by Extracting Winners and Losers from Legislative Texts. ACL (1) 2022: 270-284 - [c69]Nikhil Mehta, Maria Leonor Pacheco, Dan Goldwasser:
Tackling Fake News Detection by Continually Improving Social Context Representations using Graph Neural Networks. ACL (1) 2022: 1363-1380 - [c68]Tunazzina Islam, Dan Goldwasser:
Understanding COVID-19 Vaccine Campaign on Facebook using Minimal Supervision. IEEE Big Data 2022: 585-595 - [c67]Maria Leonor Pacheco, Shamik Roy, Dan Goldwasser:
Hands-On Interactive Neuro-Symbolic NLP with DRaiL. EMNLP (Demos) 2022: 371-378 - [c66]Younghun Lee, Dan Goldwasser:
Towards Explaining Subjective Ground of Individuals on Social Media. EMNLP (Findings) 2022: 1752-1766 - [c65]Tunazzina Islam, Dan Goldwasser:
Twitter User Representation Using Weakly Supervised Graph Embedding. ICWSM 2022: 358-369 - [c64]Maria Leonor Pacheco, Tunazzina Islam, Monal Mahajan, Andrey Shor, Ming Yin, Lyle H. Ungar, Dan Goldwasser:
A Holistic Framework for Analyzing the COVID-19 Vaccine Debate. NAACL-HLT 2022: 5821-5839 - [c63]Maria Leonor Pacheco, Max von Hippel, Ben Weintraub, Dan Goldwasser, Cristina Nita-Rotaru:
Automated Attack Synthesis by Extracting Finite State Machines from Protocol Specification Documents. SP 2022: 51-68 - [i26]Maria Leonor Pacheco, Max von Hippel, Ben Weintraub, Dan Goldwasser, Cristina Nita-Rotaru:
Automated Attack Synthesis by Extracting Finite State Machines from Protocol Specification Documents. CoRR abs/2202.09470 (2022) - [i25]Maria Leonor Pacheco, Tunazzina Islam, Monal Mahajan, Andrey Shor, Ming Yin, Lyle H. Ungar, Dan Goldwasser:
A Holistic Framework for Analyzing the COVID-19 Vaccine Debate. CoRR abs/2205.01817 (2022) - [i24]Tunazzina Islam, Dan Goldwasser:
Understanding COVID-19 Vaccine Campaign on Facebook using Minimal Supervision. CoRR abs/2210.10031 (2022) - [i23]Tunazzina Islam, Shamik Roy, Dan Goldwasser:
Weakly Supervised Learning for Analyzing Political Campaigns on Facebook. CoRR abs/2210.10669 (2022) - [i22]Younghun Lee, Dan Goldwasser:
Towards Explaining Subjective Ground of Individuals on Social Media. CoRR abs/2211.09953 (2022) - 2021
- [j8]Maria Leonor Pacheco, Dan Goldwasser:
Modeling Content and Context with Deep Relational Learning. Trans. Assoc. Comput. Linguistics 9: 100-119 (2021) - [j7]Gaurav Nanda, Kerrie A. Douglas, David R. Waller, Hillary E. Merzdorf, Dan Goldwasser:
Analyzing Large Collections of Open-Ended Feedback From MOOC Learners Using LDA Topic Modeling and Qualitative Analysis. IEEE Trans. Learn. Technol. 14(2): 146-160 (2021) - [c62]Chang Li, Dan Goldwasser:
Using Social and Linguistic Information to Adapt Pretrained Representations for Political Perspective Identification. ACL/IJCNLP (Findings) 2021: 4569-4579 - [c61]Shamik Roy, Dan Goldwasser:
Analysis of Nuanced Stances and Sentiment Towards Entities of US Politicians through the Lens of Moral Foundation Theory. SocialNLP@NAACL 2021: 1-13 - [c60]Manuel Widmoser, Maria Leonor Pacheco, Jean Honorio, Dan Goldwasser:
Randomized Deep Structured Prediction for Discourse-Level Processing. EACL 2021: 1174-1184 - [c59]Rajkumar Pujari, Dan Goldwasser:
Understanding Politics via Contextualized Discourse Processing. EMNLP (1) 2021: 1353-1367 - [c58]Shamik Roy, Maria Leonor Pacheco, Dan Goldwasser:
Identifying Morality Frames in Political Tweets using Relational Learning. EMNLP (1) 2021: 9939-9958 - [c57]Tunazzina Islam, Dan Goldwasser:
Analysis of Twitter Users' Lifestyle Choices using Joint Embedding Model. ICWSM 2021: 242-253 - [c56]I-Ta Lee, Maria Leonor Pacheco, Dan Goldwasser:
Modeling Human Mental States with an Entity-based Narrative Graph. NAACL-HLT 2021: 4916-4926 - [i21]Manuel Widmoser, Maria Leonor Pacheco, Jean Honorio, Dan Goldwasser:
Randomized Deep Structured Prediction for Discourse-Level Processing. CoRR abs/2101.10435 (2021) - [i20]Tunazzina Islam, Dan Goldwasser:
Analysis of Twitter Users' Lifestyle Choices using Joint Embedding Model. CoRR abs/2104.03189 (2021) - [i19]I-Ta Lee, Maria Leonor Pacheco, Dan Goldwasser:
Modeling Human Mental States with an Entity-based Narrative Graph. CoRR abs/2104.07079 (2021) - [i18]Tunazzina Islam, Dan Goldwasser:
Twitter User Representation using Weakly Supervised Graph Embedding. CoRR abs/2108.08988 (2021) - [i17]Shamik Roy, Maria Leonor Pacheco, Dan Goldwasser:
Identifying Morality Frames in Political Tweets using Relational Learning. CoRR abs/2109.04535 (2021) - 2020
- [j6]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) - [j5]Luke S. Snyder, Yi-Shan Lin, Morteza Karimzadeh, Dan Goldwasser, David S. Ebert:
Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness. IEEE Trans. Vis. Comput. Graph. 26(1): 558-568 (2020) - [c55]Maryam Davoodi, Eric Waltenburg, Dan Goldwasser:
Understanding the Language of Political Agreement and Disagreement in Legislative Texts. ACL 2020: 5358-5368 - [c54]Tunazzina Islam, Dan Goldwasser:
Does Yoga Make You Happy? Analyzing Twitter User Happiness using Textual and Temporal Information. IEEE BigData 2020: 4241-4249 - [c53]Aldo Porco, Dan Goldwasser:
Predicting Stance Change Using Modular Architectures. COLING 2020: 396-406 - [c52]Jiapeng Liu, Xiao Zhang, Dan Goldwasser, Xiao Wang:
Cross-Lingual Document Retrieval with Smooth Learning. COLING 2020: 3616-3629 - [c51]Xiao Zhang, Dan Goldwasser:
Semi-supervised Autoencoding Projective Dependency Parsing. COLING 2020: 3868-3885 - [c50]I-Ta Lee, Maria Leonor Pacheco, Dan Goldwasser:
Weakly-Supervised Modeling of Contextualized Event Embedding for Discourse Relations. EMNLP (Findings) 2020: 4962-4972 - [c49]Shamik Roy, Dan Goldwasser:
Weakly Supervised Learning of Nuanced Frames for Analyzing Polarization in News Media. EMNLP (1) 2020: 7698-7716 - [c48]Xiao Zhang, Dan Goldwasser:
Semi-supervised Parsing with a Variational Autoencoding Parser. IWPT 2020 2020: 40-47 - [c47]Ayush Jain, Maria Leonor Pacheco, Steven Lancette, Mahak Goindani, Dan Goldwasser:
Identifying Collaborative Conversations using Latent Discourse Behaviors. SIGdial 2020: 74-78 - [c46]Keen You, Dan Goldwasser:
"where is this relationship going?": Understanding Relationship Trajectories in Narrative Text. *SEM@COLING 2020: 168-178 - [i16]Shamik Roy, Dan Goldwasser:
Weakly Supervised Learning of Nuanced Frames for Analyzing Polarization in News Media. CoRR abs/2009.09609 (2020) - [i15]Maria Leonor Pacheco, Dan Goldwasser:
Modeling Content and Context with Deep Relational Learning. CoRR abs/2010.10453 (2020) - [i14]Keen You, Dan Goldwasser:
"where is this relationship going?": Understanding Relationship Trajectories in Narrative Text. CoRR abs/2010.15313 (2020) - [i13]Jiapeng Liu, Xiao Zhang, Dan Goldwasser, Xiao Wang:
Cross-Lingual Document Retrieval with Smooth Learning. CoRR abs/2011.00701 (2020) - [i12]Xiao Zhang, Dan Goldwasser:
Semi-supervised Autoencoding Projective Dependency Parsing. CoRR abs/2011.00704 (2020) - [i11]Tunazzina Islam, Dan Goldwasser:
Does Yoga Make You Happy? Analyzing Twitter User Happiness using Textual and Temporal Information. CoRR abs/2012.02939 (2020) - [i10]Tunazzina Islam, Dan Goldwasser:
Do You Do Yoga? Understanding Twitter Users' Types and Motivations using Social and Textual Information. CoRR abs/2012.09332 (2020) - [i9]Rajkumar Pujari, Dan Goldwasser:
Understanding Politics via Contextualized Discourse Processing. CoRR abs/2012.15784 (2020) - [i8]Rajkumar Pujari, Dan Goldwasser:
Using Natural Language Relations between Answer Choices for Machine Comprehension. CoRR abs/2012.15837 (2020)
2010 – 2019
- 2019
- [c45]Yi-Yu Lai, Jennifer Neville, Dan Goldwasser:
TransConv: Relationship Embedding in Social Networks. AAAI 2019: 4130-4138 - [c44]Samuel Jero, Maria Leonor Pacheco, Dan Goldwasser, Cristina Nita-Rotaru:
Leveraging Textual Specifications for Grammar-Based Fuzzing of Network Protocols. AAAI 2019: 9478-9483 - [c43]Xiao Zhang, Dan Goldwasser:
Sentiment Tagging with Partial Labels using Modular Architectures. ACL (1) 2019: 579-590 - [c42]Chang Li, Dan Goldwasser:
Encoding Social Information with Graph Convolutional Networks forPolitical Perspective Detection in News Media. ACL (1) 2019: 2594-2604 - [c41]I-Ta Lee, Dan Goldwasser:
Multi-Relational Script Learning for Discourse Relations. ACL (1) 2019: 4214-4226 - [c40]Xiao Zhang, Manish Marwah, I-Ta Lee, Martin F. Arlitt, Dan Goldwasser:
ACE - An Anomaly Contribution Explainer for Cyber-Security Applications. IEEE BigData 2019: 1991-2000 - [c39]Nikhil Mehta, Dan Goldwasser:
Improving Natural Language Interaction with Robots Using Advice. NAACL-HLT (1) 2019: 1962-1967 - [c38]Rajkumar Pujari, Dan Goldwasser:
Using Natural Language Relations between Answer Choices for Machine Comprehension. NAACL-HLT (1) 2019: 4010-4015 - [i7]Nikhil Mehta, Dan Goldwasser:
Improving Natural Language Interaction with Robots Using Advice. CoRR abs/1905.04655 (2019) - [i6]Xiao Zhang, Dan Goldwasser:
Sentiment Tagging with Partial Labels using Modular Architectures. CoRR abs/1906.00534 (2019) - [i5]Luke S. Snyder, Yi-Shan Lin, Morteza Karimzadeh, Dan Goldwasser, David S. Ebert:
Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness. CoRR abs/1908.02588 (2019) - [i4]Xiao Zhang, Manish Marwah, I-Ta Lee, Martin F. Arlitt, Dan Goldwasser:
An Anomaly Contribution Explainer for Cyber-Security Applications. CoRR abs/1912.00314 (2019) - 2018
- [j4]Christopher N. Gutierrez, Taegyu Kim, Raffaele Della Corte, Jeffrey Avery, Dan Goldwasser, Marcello Cinque, Saurabh Bagchi:
Learning from the Ones that Got Away: Detecting New Forms of Phishing Attacks. IEEE Trans. Dependable Secur. Comput. 15(6): 988-1001 (2018) - [c37]I-Ta Lee, Dan Goldwasser:
FEEL: Featured Event Embedding Learning. AAAI 2018: 4840-4847 - [c36]Kristen Johnson, Dan Goldwasser:
Classification of Moral Foundations in Microblog Political Discourse. ACL (1) 2018: 720-730 - [c35]Chang Li, Aldo Porco, Dan Goldwasser:
Structured Representation Learning for Online Debate Stance Prediction. COLING 2018: 3728-3739 - [c34]Gaurav Nanda, Nathan M. Hicks, David R. Waller, Kerrie Anna Douglas, Dan Goldwasser:
Understanding Learners' Opinion about Participation Certificates in Online Courses using Topic Modeling. EDM 2018 - [i3]Samuel Jero, Maria Leonor Pacheco, Dan Goldwasser, Cristina Nita-Rotaru:
Leveraging Textual Specifications for Grammar-based Fuzzing of Network Protocols. CoRR abs/1810.04755 (2018) - 2017
- [c33]Kristen Johnson, Di Jin, Dan Goldwasser:
Leveraging Behavioral and Social Information for Weakly Supervised Collective Classification of Political Discourse on Twitter. ACL (1) 2017: 741-752 - [c32]Kristen Johnson, I-Ta Lee, Dan Goldwasser:
Ideological Phrase Indicators for Classification of Political Discourse Framing on Twitter. NLP+CSS@ACL 2017: 90-99 - [c31]Ayush Patwari, Dan Goldwasser, Saurabh Bagchi:
TATHYA: A Multi-Classifier System for Detecting Check-Worthy Statements in Political Debates. CIKM 2017: 2259-2262 - [c30]Xiao Zhang, Yong Jiang, Hao Peng, Kewei Tu, Dan Goldwasser:
Semi-supervised Structured Prediction with Neural CRF Autoencoder. EMNLP 2017: 1701-1711 - [c29]Kristen Johnson, Di Jin, Dan Goldwasser:
Modeling of Political Discourse Framing on Twitter. ICWSM 2017: 556-559 - [c28]I-Ta Lee, Mahak Goindani, Chang Li, Di Jin, Kristen Johnson, Xiao Zhang, Maria Leonor Pacheco, Dan Goldwasser:
PurdueNLP at SemEval-2017 Task 1: Predicting Semantic Textual Similarity with Paraphrase and Event Embeddings. SemEval@ACL 2017: 198-202 - 2016
- [j3]Dan Goldwasser, Xiao Zhang:
Understanding Satirical Articles Using Common-Sense. Trans. Assoc. Comput. Linguistics 4: 537-549 (2016) - [c27]Snigdha Chaturvedi, Dan Goldwasser, Hal Daumé III:
Ask, and Shall You Receive? Understanding Desire Fulfillment in Natural Language Text. AAAI 2016: 2697-2703 - [c26]Kristen Johnson, Dan Goldwasser:
Identifying Stance by Analyzing Political Discourse on Twitter. NLP+CSS@EMNLP 2016: 66-75 - [c25]Kristen Johnson, Dan Goldwasser:
"All I know about politics is what I read in Twitter": Weakly Supervised Models for Extracting Politicians' Stances From Twitter. COLING 2016: 2966-2977 - [c24]Maria Leonor Pacheco, I-Ta Lee, Xiao Zhang, Abdullah Khan Zehady, Pranjal Daga, Di Jin, Ayush Parolia, Dan Goldwasser:
Adapting Event Embedding for Implicit Discourse Relation Recognition. CoNLL Shared Task 2016: 136-142 - [c23]Xiao Zhang, Maria Leonor Pacheco, Chang Li, Dan Goldwasser:
Introducing DRAIL - a Step Towards Declarative Deep Relational Learning. SPNLP@EMNLP 2016: 54-62 - [c22]Yi-Yu Lai, Chang Li, Dan Goldwasser, Jennifer Neville:
Better Together: Combining Language and Social Interactions into a Shared Representation. TextGraphs@NAACL-HLT 2016: 29-33 - 2015
- [i2]Snigdha Chaturvedi, Dan Goldwasser, Hal Daumé III:
Ask, and shall you receive? Understanding Desire Fulfillment in Natural Language Text. CoRR abs/1511.09460 (2015) - 2014
- [j2]Dan Goldwasser, Dan Roth:
Learning from natural instructions. Mach. Learn. 94(2): 205-232 (2014) - [c21]Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daumé III, Lise Getoor:
Learning Latent Engagement Patterns of Students in Online Courses. AAAI 2014: 1272-1278 - [c20]Snigdha Chaturvedi, Dan Goldwasser, Hal Daumé III:
Predicting Instructor's Intervention in MOOC forums. ACL (1) 2014: 1501-1511 - [c19]Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daumé III, Lise Getoor:
Understanding MOOC Discussion Forums using Seeded LDA. BEA@ACL 2014: 28-33 - [c18]Dan Goldwasser, Hal Daumé III:
"I Object!" Modeling Latent Pragmatic Effects in Courtroom Dialogues. EACL 2014: 655-663 - [c17]Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daumé III, Lise Getoor:
Uncovering hidden engagement patterns for predicting learner performance in MOOCs. L@S 2014: 157-158 - [c16]Zhengzheng Xu, Dan Goldwasser, Benjamin B. Bederson, Jimmy Lin:
Visual analytics of MOOCs at maryland. L@S 2014: 195-196 - 2013
- [c15]Dan Goldwasser, Dan Roth:
Leveraging Domain-Independent Information in Semantic Parsing. ACL (2) 2013: 462-466 - 2012
- [b1]Dan Goldwasser:
Learning from natural instructions. University of Illinois Urbana-Champaign, USA, 2012 - [c14]Dan Goldwasser, Vivek Srikumar, Dan Roth:
Predicting Structures in NLP: Constrained Conditional Models and Integer Linear Programming in NLP. HLT-NAACL 2012 - 2011
- [j1]Peleg Yiftachel, Irit Hadar, Dan Peled, Eitan Farchi, Dan Goldwasser:
The Study of Resource Allocation among Software Development Phases: An Economics-Based Approach. Adv. Softw. Eng. 2011: 579292:1-579292:21 (2011) - [c13]Dan Goldwasser, Roi Reichart, James Clarke, Dan Roth:
Confidence Driven Unsupervised Semantic Parsing. ACL 2011: 1486-1495 - [c12]Dan Goldwasser, Dan Roth:
Learning from Natural Instructions. IJCAI 2011: 1794-1800 - [c11]Ming-Wei Chang, James Clarke, Dan Goldwasser, Lev-Arie Ratinov, Vivek Srikumar, Dan Roth:
Structured prediction with indirect supervision. MLSLP 2011 - 2010
- [c10]James Clarke, Dan Goldwasser, Ming-Wei Chang, Dan Roth:
Driving Semantic Parsing from the World's Response. CoNLL 2010: 18-27 - [c9]Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Dan Roth:
Structured Output Learning with Indirect Supervision. ICML 2010: 199-206 - [c8]Ming-Wei Chang, Dan Goldwasser, Dan Roth, Vivek Srikumar:
Discriminative Learning over Constrained Latent Representations. HLT-NAACL 2010: 429-437
2000 – 2009
- 2009
- [c7]Jacob Eisenstein, James Clarke, Dan Goldwasser, Dan Roth:
Reading to Learn: Constructing Features from Semantic Abstracts. EMNLP 2009: 958-967 - [c6]Ming-Wei Chang, Dan Goldwasser, Dan Roth, Yuancheng Tu:
Unsupervised Constraint Driven Learning For Transliteration Discovery. HLT-NAACL 2009: 299-307 - [i1]Mark Sammons, V. G. Vinod Vydiswaran, Tim Vieira, Nikhil Johri, Ming-Wei Chang, Dan Goldwasser, Vivek Srikumar, Gourab Kundu, Yuancheng Tu, Kevin Small, Joshua S. Rule, Quang Do, Dan Roth:
Relation Alignment for Textual Entailment Recognition. TAC 2009 - 2008
- [c5]Dan Goldwasser, Dan Roth:
Active Sample Selection for Named Entity Transliteration. ACL (2) 2008: 53-56 - [c4]Dan Goldwasser, Dan Roth:
Transliteration as Constrained Optimization. EMNLP 2008: 353-362 - [c3]Dan Goldwasser, Ofer Strichman, Shai Fine:
A Theory-Based Decision Heuristic for DPLL(T). FMCAD 2008: 1-8 - 2007
- [c2]Massimo Zancanaro, Tsvi Kuflik, Zvi Boger, Dina Goren-Bar, Dan Goldwasser:
Analyzing Museum Visitors' Behavior Patterns. User Modeling 2007: 238-246 - 2006
- [c1]Shlomo Berkovsky, Dan Goldwasser, Tsvi Kuflik, Francesco Ricci:
Identifying Inter-Domain Similarities Through Content-Based Analysis of Hierarchical Web-Directories. ECAI 2006: 789-790
Coauthor Index
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