computational language understanding lab


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  2021 (12)
Triplet-Trained Vector Space and Sieve-Based Search Improve Biomedical Concept Normalization. Xu, D.; and Bethard, S. In Proceedings of the 20th Workshop on Biomedical Language Processing, pages 11–22, Online, June 2021. Association for Computational Linguistics
Triplet-Trained Vector Space and Sieve-Based Search Improve Biomedical Concept Normalization [link]Paper   bibtex  
EntityBERT: Entity-centric Masking Strategy for Model Pretraining for the Clinical Domain. Lin, C.; Miller, T.; Dligach, D.; Bethard, S.; and Savova, G. In Proceedings of the 20th Workshop on Biomedical Language Processing, pages 191–201, Online, June 2021. Association for Computational Linguistics
EntityBERT: Entity-centric Masking Strategy for Model Pretraining for the Clinical Domain [link]Paper   bibtex  
Explainable Multi-hop Verbal Reasoning Through Internal Monologue. Liang, Z.; Bethard, S.; and Surdeanu, M. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1225–1250, Online, June 2021. Association for Computational Linguistics [Acceptance rate 26%]
Explainable Multi-hop Verbal Reasoning Through Internal Monologue [link]Paper   bibtex  
If You Want to Go Far Go Together: Unsupervised Joint Candidate Evidence Retrieval for Multi-hop Question Answering. Yadav, V.; Bethard, S.; and Surdeanu, M. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 4571–4581, Online, June 2021. Association for Computational Linguistics [Acceptance rate 26%]
If You Want to Go Far Go Together: Unsupervised Joint Candidate Evidence Retrieval for Multi-hop Question Answering [link]Paper   bibtex  
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Toutanova, K.; Rumshisky, A.; Zettlemoyer, L.; Hakkani-Tur, D.; Beltagy, I.; Bethard, S.; Cotterell, R.; Chakraborty, T.; and Zhou, Y., editors. Association for Computational Linguistics. Online, June 2021.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies [link]Paper   bibtex  
Domain adaptation in practice: Lessons from a real-world information extraction pipeline. Miller, T.; Laparra, E.; and Bethard, S. In Proceedings of the Second Workshop on Domain Adaptation for NLP, pages 105–110, Kyiv, Ukraine, April 2021. Association for Computational Linguistics
Domain adaptation in practice: Lessons from a real-world information extraction pipeline [link]Paper   bibtex  
Consumer Cynicism Identification for Spanish Reviews using a Spanish Transformer Model. González-López, S.; Bethard, S.; Orozco, F. C. E.; and López-Monroy, A. P. Procesamiento del Lenguaje Natural, 66(0): 111–120. 2021.
Consumer Cynicism Identification for Spanish Reviews using a Spanish Transformer Model [link]Paper   bibtex  
Data and Model Distillation as a Solution for Domain-transferable Fact Verification. Mithun, M.; Suntwal, S.; and Surdeanu, M. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021.
Data and Model Distillation as a Solution for Domain-transferable Fact Verification [pdf]Paper   bibtex  
Using the Hammer Only on Nails: A Hybrid Method for Representation-based Evidence Retrieval for Question Answering. Liang, Z.; Zhao, Y.; and Surdeanu, M. In Proceedings of 43rd European Conference on IR Research, ECIR 2021, 2021.
Using the Hammer Only on Nails: A Hybrid Method for Representation-based Evidence Retrieval for Question Answering [pdf]Paper   bibtex  
Interpretability Rules: Jointly Bootstrapping a Neural Relation Extractor with an Explanation Decoder. Tang, Z.; and Surdeanu, M. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: TrustNLP Workshop, 2021.
Interpretability Rules: Jointly Bootstrapping a Neural Relation Extractor with an Explanation Decoder [pdf]Paper   bibtex  
Me, myself, and ire: Effects of automatic transcription quality on emotion, sarcasm, and personality detection. Culnan, J.; Park, S.; Krishnaswamy, M.; and Sharp, R. In Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 250–256, April 2021.
Me, myself, and ire: Effects of automatic transcription quality on emotion, sarcasm, and personality detection [link]Paper   bibtex  
Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading. Van, H.; Yadav, V.; and Surdeanu, M. ArXiv, abs/2106.04134. 2021.
Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading [pdf]Paper   bibtex  
  2020 (19)
TTUI at SemEval-2020 Task 11: Propaganda Detection with Transfer Learning and Ensembles. Kim, M.; and Bethard, S. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1829–1834, Barcelona (online), December 2020. International Committee for Computational Linguistics
TTUI at SemEval-2020 Task 11: Propaganda Detection with Transfer Learning and Ensembles [link]Paper   bibtex  
Proceedings of the 3rd Clinical Natural Language Processing Workshop. Rumshisky, A.; Roberts, K.; Bethard, S.; and Naumann, T., editors. Association for Computational Linguistics. Online, November 2020.
Proceedings of the 3rd Clinical Natural Language Processing Workshop [link]Paper   bibtex  
A Dataset and Evaluation Framework for Complex Geographical Description Parsing. Laparra, E.; and Bethard, S. In Proceedings of the 28th International Conference on Computational Linguistics, pages 936–948, Barcelona, Spain (Online), December 2020. International Committee on Computational Linguistics
A Dataset and Evaluation Framework for Complex Geographical Description Parsing [link]Paper   bibtex  
An Analysis of Capsule Networks for Part of Speech Tagging in High- and Low-resource Scenarios. Zupon, A.; Rafique, F.; and Surdeanu, M. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Workshop on Insights from Negative Results in NLP, 2020.
An Analysis of Capsule Networks for Part of Speech Tagging in High- and Low-resource Scenarios [pdf]Paper   bibtex  
Do Transformers Dream of Inference, or Can Pretrained Generative Models Learn Implicit Inferential Rules?. Liang, Z.; and Surdeanu, M. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Workshop on Insights from Negative Results in NLP, 2020.
Do Transformers Dream of Inference, or Can Pretrained Generative Models Learn Implicit Inferential Rules? [pdf]Paper   bibtex  
The Language of Food during the Pandemic: Hints about the Dietary Effects of Covid-19. Van, H.; Musa, A.; Surdeanu, M.; and Kobourov, S. arXiv preprint arXiv:2010.07466. 2020.
The Language of Food during the Pandemic: Hints about the Dietary Effects of Covid-19 [link]Paper   bibtex  
Using the Hammer Only on Nails: A Hybrid Method for Evidence Retrieval for Question Answering. Liang, Z.; Zhao, Y.; and Surdeanu, M. arXiv preprint arXiv:2009.10791. 2020.
Using the Hammer Only on Nails: A Hybrid Method for Evidence Retrieval for Question Answering [link]Paper   bibtex  
Having Your Cake and Eating it Too: Training Neural Retrieval for Language Inference without Losing Lexical Match. Yadav, V.; Bethard, S.; and Surdeanu, M. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1625–1628, 2020. Erratum: the PDF linked here contains the proper support acknowledgment as well as a COI statement for one of the authors, which are missing in the SIGIR camera-ready paper.
Having Your Cake and Eating it Too: Training Neural Retrieval for Language Inference without Losing Lexical Match [pdf]Paper   bibtex  
Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)–based ranking for concept normalization. Xu, D.; Gopale, M.; Zhang, J.; Brown, K.; Begoli, E.; and Bethard, S. Journal of the American Medical Informatics Association. 07 2020.
Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)–based ranking for concept normalization [link]Paper   doi   bibtex  
A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction. Lin, C.; Miller, T.; Dligach, D.; Sadeque, F.; Bethard, S.; and Savova, G. In Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing, pages 70-75, Online, July 2020. Association for Computational Linguistics
A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction [link]Paper   bibtex  
Assisting Undergraduate Students in Writing Spanish Methodology Sections. González-López, S.; Bethard, S.; and Lopez-Lopez, A. In Proceedings of the Fifteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 115-123, Seattle, WA, USA, July 2020. Association for Computational Linguistics
Assisting Undergraduate Students in Writing Spanish Methodology Sections [link]Paper   bibtex  
A Generate-and-Rank Framework with Semantic Type Regularization for Biomedical Concept Normalization. Xu, D.; Zhang, Z.; and Bethard, S. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8452-8464, Online, July 2020. Association for Computational Linguistics
A Generate-and-Rank Framework with Semantic Type Regularization for Biomedical Concept Normalization [link]Paper   bibtex  
How does BERT's attention change when you fine-tune? An analysis methodology and a case study in negation scope. Zhao, Y.; and Bethard, S. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4729-4747, Online, July 2020. Association for Computational Linguistics
How does BERT's attention change when you fine-tune? An analysis methodology and a case study in negation scope [link]Paper   bibtex  
Unsupervised Alignment-based Iterative Evidence Retrieval for Multi-hop Question Answering. Yadav, V.; Bethard, S.; and Surdeanu, M. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4514-4525, Online, July 2020. Association for Computational Linguistics
Unsupervised Alignment-based Iterative Evidence Retrieval for Multi-hop Question Answering [link]Paper   bibtex  
Rethinking domain adaptation for machine learning over clinical language. Laparra, E.; Bethard, S.; and Miller, T. A JAMIA Open. 04 2020.
Rethinking domain adaptation for machine learning over clinical language [link]Paper   doi   bibtex  
Does BERT need domain adaptation for clinical negation detection?. Lin, C.; Bethard, S.; Dligach, D.; Sadeque, F.; Savova, G.; and Miller, T. A Journal of the American Medical Informatics Association. 02 2020. ocaa001
Does BERT need domain adaptation for clinical negation detection? [link]Paper   doi   bibtex  
Parsing as Tagging. Vacareanu, R.; Barbosa, G. C. G.; Valenzuela-Escarcega, M. A.; and Surdeanu, M. In Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC), 2020.
Parsing as Tagging [pdf]Paper   bibtex  
Exploring Interpretability in Event Extraction: Multitask Learning of a Neural Event Classifier and an Explanation Decoder. Tang, Z.; Hahn-Powell, G.; and Surdeanu, M. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, Seattle, United States, July 2020. Association for Computational Linguistics
Exploring Interpretability in Event Extraction: Multitask Learning of a Neural Event Classifier and an Explanation Decoder [pdf]Paper   bibtex  
An Unsupervised Method for Learning Representations of Multi-word Expressions for Semantic Classification. Vacareanu, R.; Valenzuela-Escarcega, M. A.; Sharp, R.; and Surdeanu, M. In The 28th International Conference on Computational Linguistics in Barcelona (COLING 2020), 2020.
An Unsupervised Method for Learning Representations of Multi-word Expressions for Semantic Classification [pdf]Paper   bibtex  
  2019 (15)
Enabling Search and Collaborative Assembly of Causal Interactions Extracted from Multilingual and Multi-domain Free Text. Barbosa, G. C.; Wong, Z.; Hahn-Powell, G.; Bell, D.; Sharp, R.; Valenzuela-Escarcega, M. A.; and Surdeanu, M. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT): Software Demonstrations, 2019. This paper received the Best System Demonstration award
Enabling Search and Collaborative Assembly of Causal Interactions Extracted from Multilingual and Multi-domain Free Text [pdf]Paper   bibtex  
Understanding the Polarity of Events in the Biomedical Literature: Deep Learning vs. Linguistically-informed Methods. Noriega-Atala, E.; Liang, Z.; Bachman, J. A.; Morrison, C. T.; and Surdeanu, M. In Proceedings of the Workshop on Extracting Structured Knowledge from Scientific Publications, 2019. NAACL-HLT
Understanding the Polarity of Events in the Biomedical Literature: Deep Learning vs. Linguistically-informed Methods [pdf]Paper   bibtex  
Semi-Supervised Teacher-Student Architecture for Relation Extraction. Luo, F.; Nagesh, A.; Sharp, R.; and Surdeanu, M. In Proceedings of the 3rd Workshop on Structured Prediction for Natural Language Processing, 2019. NAACL-HLT
Semi-Supervised Teacher-Student Architecture for Relation Extraction [pdf]Paper   bibtex  
Lightly Supervised Representation Learning with Global Interpretability. Zupon, A.; Alexeeva, M.; Valenzuela-Escarcega, M. A.; Nagesh, A.; and Surdeanu, M. In Proceedings of the 3rd Workshop on Structured Prediction for Natural Language Processing, 2019. NAACL-HLT
Lightly Supervised Representation Learning with Global Interpretability [pdf]Paper   bibtex  
Proceedings of the 2nd Clinical Natural Language Processing Workshop. Rumshisky, A.; Roberts, K.; Bethard, S.; and Naumann, T., editors. Association for Computational Linguistics, Minneapolis, Minnesota, USA, 6 2019.
Proceedings of the 2nd Clinical Natural Language Processing Workshop [link]Paper   bibtex  
Inferring missing metadata from environmental policy texts. Bethard, S.; Laparra, E.; Wang, S.; Zhao, Y.; Al-Ghezi, R.; Lien, A.; and Lopez-Hoffman, L. In Proceedings of the 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 46-51, Minneapolis, USA, 6 2019. Association for Computational Linguistics
Inferring missing metadata from environmental policy texts [link]Paper   bibtex  
A BERT-based Universal Model for Both Within- and Cross-sentence Clinical Temporal Relation Extraction. Lin, C.; Miller, T.; Dligach, D.; Bethard, S.; and Savova, G. In Proceedings of the 2nd Clinical Natural Language Processing Workshop, pages 65-71, Minneapolis, Minnesota, USA, 6 2019. Association for Computational Linguistics
A BERT-based Universal Model for Both Within- and Cross-sentence Clinical Temporal Relation Extraction [link]Paper   bibtex  
University of Arizona at SemEval-2019 Task 12: Deep-Affix Named Entity Recognition of Geolocation Entities. Yadav, V.; Laparra, E.; Wang, T.; Surdeanu, M.; and Bethard, S. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1319-1323, Minneapolis, Minnesota, USA, 6 2019. Association for Computational Linguistics
University of Arizona at SemEval-2019 Task 12: Deep-Affix Named Entity Recognition of Geolocation Entities [link]Paper   bibtex  
Incivility Detection in Online Comments. Sadeque, F.; Rains, S.; Shmargad, Y.; Kenski, K.; Coe, K.; and Bethard, S. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 283-291, Minneapolis, Minnesota, 6 2019. Association for Computational Linguistics
Incivility Detection in Online Comments [link]Paper   bibtex  
Pre-trained Contextualized Character Embeddings Lead to Major Improvements in Time Normalization: a Detailed Analysis. Xu, D.; Laparra, E.; and Bethard, S. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 68-74, Minneapolis, Minnesota, 6 2019. Association for Computational Linguistics
Pre-trained Contextualized Character Embeddings Lead to Major Improvements in Time Normalization: a Detailed Analysis [link]Paper   bibtex  
Eidos, INDRA, & Delphi: From Free Text to Executable Causal Models. Sharp, R.; Pyarelal, A.; Gyori, B.; Alcock, K.; Laparra, E.; Valenzuela-Escarcega, M. A.; Nagesh, A.; Yadav, V.; Bachman, J.; Tang, Z.; Lent, H.; Luo, F.; Paul, M.; Bethard, S.; Barnard, K.; Morrison, C.; and Surdeanu, M. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations), pages 42-47, Minneapolis, Minnesota, 6 2019. Association for Computational Linguistics
Eidos, INDRA, & Delphi: From Free Text to Executable Causal Models [link]Paper   bibtex  
Alignment over Heterogeneous Embeddings for Question Answering. Yadav, V.; Bethard, S.; and Surdeanu, M. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 2681-2691, Minneapolis, Minnesota, 6 2019. Association for Computational Linguistics
Alignment over Heterogeneous Embeddings for Question Answering [link]Paper   bibtex  
Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering. Yadav, V.; Bethard, S.; and Surdeanu, M. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, (Long Papers), Hong Kong, November 2019. Association for Computational Linguistics
Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering [pdf]Paper   Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering [pdf] poster   bibtex  
What does the language of foods say about us?. Van, H.; Musa, A.; Chen, H.; Surdeanu, M.; and Kobourov, S. In Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI), 2019.
What does the language of foods say about us? [pdf]Paper   What does the language of foods say about us? [pptx] slides   bibtex  
On the Importance of Delexicalization for Fact Verification. Suntwal, S.; Paul, M.; Sharp, R.; and Surdeanu, M. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 3413-3418, Hong Kong, China, November 2019. Association for Computational Linguistics
On the Importance of Delexicalization for Fact Verification [link]Paper   doi   bibtex  
  2018 (23)
Effects of Message Framing on Diabetes Screening Attitudes and Behavior. Rains, S. A.; Hingle, M. D.; Surdeanu, M.; Bell, D.; and Kobourov, S. Manuscript in preparation. 2018.
Effects of Message Framing on Diabetes Screening Attitudes and Behavior [pdf]Paper   bibtex  
Lightly-supervised Representation Learning with Global Interpretability. Valenzuela-Escarcega, M. A; Nagesh, A.; and Surdeanu, M. In arXiv, 2018.
Lightly-supervised Representation Learning with Global Interpretability [link]Paper   bibtex  
A Test of The Risk Perception Attitude Framework as a Message Tailoring Strategy to Promote Diabetes Screening. Rains, S. A.; Hingle, M. D.; Surdeanu, M.; Bell, D.; and Kobourov, S. Health Communication. 2018.
A Test of The Risk Perception Attitude Framework as a Message Tailoring Strategy to Promote Diabetes Screening [pdf]Paper   A Test of The Risk Perception Attitude Framework as a Message Tailoring Strategy to Promote Diabetes Screening [link] odi   bibtex  
WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-hop Inference. Jansen, P.; Wainwright, E.; Marmorstein, S.; and Morrison, C. T. In Proceedings of the 11th International Conference on Language Resources and Evaluation (LREC), 2018.
WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-hop Inference [pdf]Paper   WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-hop Inference [link] code   bibtex  
Controlling Information Aggregation for Complex Question Answering. Kwon, H.; Trivedi, H.; Jansen, P.; Surdeanu, M.; and Balasubramanian, N. In Proceedings of the 40th European Conference on Information Retrieval (ECIR), 2018.
Controlling Information Aggregation for Complex Question Answering [pdf]Paper   bibtex  
Text Annotation Graphs: Annotating Complex Natural Language Phenomena. Forbes, A. G.; Lee, K.; Hahn-Powell, G.; Valenzuela-Escarcega, M. A.; and Surdeanu, M. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC'18), Miyazaki, Japan, May 2018. European Language Resources Association (ELRA)
Text Annotation Graphs: Annotating Complex Natural Language Phenomena [link] code   Text Annotation Graphs: Annotating Complex Natural Language Phenomena [pdf]Paper   bibtex  
Keep your bearings: Lightly-supervised Information Extraction with Ladder Networks that avoids Semantic Drift. Nagesh, A.; and Surdeanu, M. In NAACL HLT 2018, The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, New Orleans, Louisiana, USA, Jun 1 - June 6, 2018, 2018.
Keep your bearings: Lightly-supervised Information Extraction with Ladder Networks that avoids Semantic Drift [pdf]Paper   bibtex  
Scientific Discovery as Link Prediction in Influence and Citation Graphs. Luo, F.; Valenzuela-Escarcega, M. A.; Hahn-Powell, G.; and Surdeanu, M. In TextGraphs: 12th Workshop on Graph-Based Natural Language Processing, 2018. NAACL
Scientific Discovery as Link Prediction in Influence and Citation Graphs [pdf] slides   Scientific Discovery as Link Prediction in Influence and Citation Graphs [pdf]Paper   bibtex   abstract  
Sanity Check: A Strong Alignment and Information Retrieval Baseline for AI2 Reasoning Challenge. Yadav, V.; Sharp, R.; and Surdeanu, M. . 2018.
Sanity Check: A Strong Alignment and Information Retrieval Baseline for AI2 Reasoning Challenge [pdf]Paper   bibtex  
CUILESS2016: a clinical corpus applying compositional normalization of text mentions. Osborne, J. D.; Neu, M. B.; Danila, M. I.; Solorio, T.; and Bethard, S. J. Journal of Biomedical Semantics, 9(1): 2. Jan 2018.
CUILESS2016: a clinical corpus applying compositional normalization of text mentions [link]Paper   doi   bibtex  
Measuring the Latency of Depression Detection in Social Media. Sadeque, F.; Xu, D.; and Bethard, S. In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, of WSDM '18, pages 495-503, New York, NY, USA, 2018. ACM
Measuring the Latency of Depression Detection in Social Media [link]Paper   doi   bibtex  
Proceedings of The 12th International Workshop on Semantic Evaluation. Apidianaki, M.; Mohammad, S. M.; May, J.; Shutova, E.; Bethard, S.; and Carpuat, M., editors. Association for Computational Linguistics, 6 2018.
Proceedings of The 12th International Workshop on Semantic Evaluation [link]Paper   bibtex  
SemEval 2018 Task 6: Parsing Time Normalizations. Laparra, E.; Xu, D.; Elsayed, A.; Bethard, S.; and Palmer, M. In Proceedings of The 12th International Workshop on Semantic Evaluation, pages 88-96, 6 2018. Association for Computational Linguistics
SemEval 2018 Task 6: Parsing Time Normalizations [link]Paper   bibtex  
Deep Affix Features Improve Neural Named Entity Recognizers. Yadav, V.; Sharp, R.; and Bethard, S. In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, pages 167-172, 6 2018. Association for Computational Linguistics
Deep Affix Features Improve Neural Named Entity Recognizers [link]Paper   bibtex  
Grounding gradable adjectives through crowdsourcing. Sharp, R.; Paul, M.; Nagesh, A.; Bell, D.; and Surdeanu, M. In Calzolari, N.; Choukri, K.; Cieri, C.; Declerck, T.; Goggi, S.; Hasida, K.; Isahara, H.; Maegaard, B.; Mariani, J.; Mazo, H.; Moreno, A.; Odijk, J.; Piperidis, S.; and Tokunaga, T., editor(s), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Paris, France, May 2018. European Language Resources Association (ELRA)
Grounding gradable adjectives through crowdsourcing [pdf]Paper   bibtex  
A Survey on Recent Advances in Named Entity Recognition from Deep Learning models. Yadav, V.; and Bethard, S. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2145-2158, 2018. Association for Computational Linguistics
A Survey on Recent Advances in Named Entity Recognition from Deep Learning models [link]Paper   bibtex  
Detecting diabetes risk from social media activity. Bell, D.; Laparra, E.; Kousik, A.; Ishihara, T.; Surdeanu, M.; and Kobourov, S. In Ninth International Workshop on Health Text Mining and Information Analysis (LOUHI), 2018.
Detecting diabetes risk from social media activity [pdf]Paper   Detecting diabetes risk from social media activity [pptx] slides   bibtex  
Calorie estimation from pictures of food: Crowdsourcing study. Zhou, J.; Bell, D.; Nusrat, S.; Hingle, M. D.; Surdeanu, M.; and Kobourov, S. Interactive Journal of Medical Research (IJMR). 2018.
Calorie estimation from pictures of food: Crowdsourcing study [pdf]Paper   doi   bibtex  
An Exploration of Three Lightly-supervised Representation Learning Approaches for Named Entity Classification. Nagesh, A.; and Surdeanu, M. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2312-2324, 2018. Association for Computational Linguistics
An Exploration of Three Lightly-supervised Representation Learning Approaches for Named Entity Classification [link]Paper   bibtex  
Large-scale Automated Machine Reading Discovers New Cancer Driving Mechanisms. Valenzuela-Escarcega, M. A.; Babur, O.; Hahn-Powell, G.; Bell, D.; Hicks, T.; Noriega-Atala, E.; Wang, X.; Surdeanu, M.; Demir, E.; and Morrison, C. T. Database: The Journal of Biological Databases and Curation. 2018.
Large-scale Automated Machine Reading Discovers New Cancer Driving Mechanisms [pdf]Paper   doi   bibtex  
Visual Supervision in Bootstrapped Information Extraction. Berger, M.; Nagesh, A.; Levine, J. A.; Surdeanu, M.; and Zhang, H. H. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
Visual Supervision in Bootstrapped Information Extraction [pdf]Paper   bibtex  
Detecting Cyber Threats in Non-English Dark Net Markets: A Cross-Lingual Transfer Learning Approach. Ebrahimi, M.; Surdeanu, M.; Samtani, S.; and Chen, H. In Proceedings of the IEEE Intelligence and Security Informatics Conference (ISI), 2018. This paper won the Best Paper Runner-up Award.
Detecting Cyber Threats in Non-English Dark Net Markets: A Cross-Lingual Transfer Learning Approach [pdf]Paper   bibtex  
Machine Reading for Scientific Discovery. Hahn-Powell, G. Ph.D. Thesis, 2018.
Machine Reading for Scientific Discovery [link]Paper   bibtex  
  2017 (17)
Representations of Time Expressions for Temporal Relation Extraction with Convolutional Neural Networks. Lin, C.; Miller, T.; Dligach, D.; Bethard, S.; and Savova, G. In BioNLP 2017, pages 322-327, Vancouver, Canada,, 8 2017. Association for Computational Linguistics
Representations of Time Expressions for Temporal Relation Extraction with Convolutional Neural Networks [link]Paper   bibtex  
Unsupervised Domain Adaptation for Clinical Negation Detection. Miller, T.; Bethard, S.; Amiri, H.; and Savova, G. In BioNLP 2017, pages 165-170, Vancouver, Canada,, 8 2017. Association for Computational Linguistics
Unsupervised Domain Adaptation for Clinical Negation Detection [link]Paper   bibtex  
Recurrent Neural Network Architectures for Event Extraction from Italian Medical Reports. Viani, N.; Miller, T. A.; Dligach, D.; Bethard, S.; Napolitano, C.; Priori, S. G.; Bellazzi, R.; Sacchi, L.; and Savova, G. K. In ten Teije, A.; Popow, C.; Holmes, J. H.; and Sacchi, L., editor(s), Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings, pages 198-202, Cham, 2017. Springer International Publishing
Recurrent Neural Network Architectures for Event Extraction from Italian Medical Reports [link]Paper   doi   bibtex  
Towards generalizable entity-centric clinical coreference resolution . Miller, T.; Dligach, D.; Bethard, S.; Lin, C.; and Savova, G. Journal of Biomedical Informatics , 69: 251 - 258. 2017.
Towards generalizable entity-centric clinical coreference resolution  [link]Paper   doi   bibtex  
Neural Temporal Relation Extraction. Dligach, D.; Miller, T.; Lin, C.; Bethard, S.; and Savova, G. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 746-751, Valencia, Spain, 4 2017. Association for Computational Linguistics
Neural Temporal Relation Extraction [link]Paper   bibtex  
SemEval-2017 Task 12: Clinical TempEval. Bethard, S.; Savova, G.; Palmer, M.; and Pustejovsky, J. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 565-572, Vancouver, Canada, 8 2017. Association for Computational Linguistics
SemEval-2017 Task 12: Clinical TempEval [link]Paper   bibtex  
Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification. Sharp, R.; Surdeanu, M.; Jansen, P.; Valenzuela-Escarcega, M. A; Clark, P.; and Hammond, M. In Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), pages 69-79, 2017.
Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification [link]Paper   bibtex  
Framing QA as Building and Ranking Intersentence Answer Justifications. Jansen, P.; Sharp, R.; Surdeanu, M.; and Clark, P. Computational Linguistics. 2017.
Framing QA as Building and Ranking Intersentence Answer Justifications [link]Paper   bibtex  
Learning what to read: Focused machine reading. Noriega-Atala, E.; Valenzuela-Escarcega, M. A; Morrison, C.; and Surdeanu, M. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2895-2900, 2017.
Learning what to read: Focused machine reading [pdf]Paper   bibtex  
A scaffolding approach to coreference resolution integrating statistical and rule-based models. Lee, H.; Surdeanu, M.; and Jurafsky, D. Natural Language Engineering,1-30. 2017.
A scaffolding approach to coreference resolution integrating statistical and rule-based models [pdf]Paper   bibtex  
Swanson linking revisited: Accelerating literature-based discovery across domains using a conceptual influence graph. Hahn-Powell, G.; Valenzuela-Escarcega, M. A; and Surdeanu, M. Proceedings of ACL 2017, System Demonstrations,103-108. 2017.
Swanson linking revisited: Accelerating literature-based discovery across domains using a conceptual influence graph [link]Paper   bibtex  
Focused Reading: Reinforcement Learning for What Documents to Read. Noriega-Atala, E.; Valenzuela-Escarcega, M. A.; Morrison, C. T.; and Surdeanu, M. In Proceedings of the Interactive Machine Learning and Semantic Information Retrieval Workshop at ICML, 2017, 2017.
Focused Reading: Reinforcement Learning for What Documents to Read [pdf]Paper   bibtex  
Large-scale automated reading with Reach discovers new cancer driving mechanisms. Valenzuela-Escarcega, M. A.; Babur, O.; Hahn-Powell, G.; Bell, D.; Hicks, T.; Noriega-Atala, E.; Wang, X.; Surdeanu, M.; Demir, E.; and Morrison, C. T. In Proceedings of the Sixth BioCreative Challenge Evaluation Workshop, pages 201-203, 2017.
Large-scale automated reading with Reach discovers new cancer driving mechanisms [pdf]Paper   bibtex  
A Study of Automatically Acquiring Explanatory Inference Patterns from Corpora of Explanations: Lessons from Elementary Science Exams. Jansen, P. In Proceedings of the 2017 Workshop on Automated Knowledge Base Construction, of AKBC'17, 2017.
A Study of Automatically Acquiring Explanatory Inference Patterns from Corpora of Explanations: Lessons from Elementary Science Exams [pdf]Paper   A Study of Automatically Acquiring Explanatory Inference Patterns from Corpora of Explanations: Lessons from Elementary Science Exams [link] data   bibtex  
Improving Implicit Semantic Role Labeling by Predicting Semantic Frame Arguments. Do, Q. N. T.; Bethard, S.; and Moens, M. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 90-99, Taipei, Taiwan, 11 2017. Asian Federation of Natural Language Processing
Improving Implicit Semantic Role Labeling by Predicting Semantic Frame Arguments [link]Paper   bibtex  
UArizona at the CLEF eRisk 2017 Pilot Task: Linear and Recurrent Models for Early Depression Detection. Sadeque, F.; Xu, D.; and Bethard, S. In CEUR workshop proceedings: Working Notes of CLEF 2017 - Conference and Labs of the Evaluation Forum, Dublin, Ireland, 9 2017.
UArizona at the CLEF eRisk 2017 Pilot Task: Linear and Recurrent Models for Early Depression Detection [pdf]Paper   bibtex  
Infusing Latent User-Concerns from User Reviews into Collaborative Filtering. Pradhan, L.; Zhang, C.; and Bethard, S. In 2017 IEEE International Conference on Information Reuse and Integration (IRI), pages 471-477, 8 2017.
Infusing Latent User-Concerns from User Reviews into Collaborative Filtering [link]Paper   doi   bibtex  
  2016 (12)
What's in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams. Jansen, P.; Balasubramanian, N.; Surdeanu, M.; and Clark, P. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2956-2965, Osaka, Japan, December 2016. The COLING 2016 Organizing Committee
What's in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams [link]Paper   What's in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams [link] data   bibtex  
Proceedings of the Clinical Natural Language Processing Workshop (ClinicalNLP). Rumshisky, A.; Roberts, K.; Bethard, S.; and Naumann, T. The COLING 2016 Organizing Committee, Osaka, Japan, 12 2016.
Proceedings of the Clinical Natural Language Processing Workshop (ClinicalNLP) [link]Paper   bibtex  
Facing the most difficult case of Semantic Role Labeling: A collaboration of word embeddings and co-training. Do, Q. N. T.; Bethard, S.; and Moens, M. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1275-1284, Osaka, Japan, 12 2016. The COLING 2016 Organizing Committee
Facing the most difficult case of Semantic Role Labeling: A collaboration of word embeddings and co-training [link]Paper   bibtex  
Why Do They Leave: Modeling Participation in Online Depression Forums. Sadeque, F.; Pedersen, T.; Solorio, T.; Shrestha, P.; Rey-Villamizar, N.; and Bethard, S. In Proceedings of The Fourth International Workshop on Natural Language Processing for Social Media, pages 14-19, Austin, TX, USA, 11 2016. Association for Computational Linguistics
Why Do They Leave: Modeling Participation in Online Depression Forums [link]Paper   bibtex  
Analysis of Anxious Word Usage on Online Health Forums. Rey-Villamizar, N.; Shrestha, P.; Sadeque, F.; Bethard, S.; Pedersen, T.; Mukherjee, A.; and Solorio, T. In Proceedings of the Seventh International Workshop on Health Text Mining and Information Analysis, pages 37-42, Auxtin, TX, 11 2016. Association for Computational Linguistics
Analysis of Anxious Word Usage on Online Health Forums [link]Paper   bibtex  
Visualizing the Content of a Children's Story in a Virtual World: Lessons Learned. Do, Q. N. T.; Bethard, S.; and Moens, M. In Proceedings of the Workshop on Uphill Battles in Language Processing: Scaling Early Achievements to Robust Methods, pages 39-42, Austin, TX, 11 2016. Association for Computational Linguistics
Visualizing the Content of a Children's Story in a Virtual World: Lessons Learned [link]Paper   bibtex  
SnapToGrid: From Statistical to Interpretable Models for Biomedical Information Extraction. Valenzuela-Escarcega, M. A.; Hahn-Powell, G.; Bell, D.; and Surdeanu, M. In Proceedings of the 2016 Workshop on Biomedical Natural Language Processing (BioNLP 2016), 2016.
SnapToGrid: From Statistical to Interpretable Models for Biomedical Information Extraction [link]Paper   bibtex  
This before That: Causal Precedence in the Biomedical Domain. Hahn-Powell, G.; Bell, D.; Valenzuela-Escarcega, M. A.; and Surdeanu, M. In Proceedings of the 2016 Workshop on Biomedical Natural Language Processing (BioNLP 2016), 2016. Latest results can be found at https://repository.arizona.edu/handle/10150/630562
This before That: Causal Precedence in the Biomedical Domain [link]Paper   bibtex  
Creating Causal Embeddings for Question Answering with Minimal Supervision. Sharp, R.; Surdeanu, M.; Jansen, P.; Clark, P.; and Hammond, M. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016.
Creating Causal Embeddings for Question Answering with Minimal Supervision [link]Paper   Creating Causal Embeddings for Question Answering with Minimal Supervision [link] data and code   bibtex  
An Investigation of Coreference Phenomena in the Biomedical Domain. Bell, D.; Hahn-Powell, G.; Valenzuela-Escarcega, M. A.; Hahn-Powell, G.; and Surdeanu, M. In Proceedings of the 10th edition of the Language Resources and Evaluation Conference (LREC), 2016.
An Investigation of Coreference Phenomena in the Biomedical Domain [pdf]Paper   An Investigation of Coreference Phenomena in the Biomedical Domain [link] code   bibtex  
Odin's Runes: A Rule Language for Information Extraction. Valenzuela-Escarcega, M. A.; Hahn-Powell, G.; and Surdeanu, M. In Proceedings of the 10th edition of the Language Resources and Evaluation Conference (LREC), 2016.
Odin's Runes: A Rule Language for Information Extraction [pdf]Paper   Odin's Runes: A Rule Language for Information Extraction [link] code   bibtex  
Towards Using Social Media to Identify Individuals at Risk for Preventable Chronic Illness. Bell, D.; Fried, D.; Huangfu, L.; Surdeanu, M.; and Kobourov, S. In Proceedings of the 10th edition of the Language Resources and Evaluation Conference (LREC), 2016.
Towards Using Social Media to Identify Individuals at Risk for Preventable Chronic Illness [pdf]Paper   Towards Using Social Media to Identify Individuals at Risk for Preventable Chronic Illness [link] code   bibtex  
  2015 (7)
Identifying meaningful citations. Valenzuela, M.; Ha, V.; and Etzioni, O. In Proceedings of the "Scholarly Big Data: AI Perspectives, Challenges, and Ideas" Workshop at the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015.
Identifying meaningful citations [pdf]Paper   bibtex  
A Domain-independent Rule-based Framework for Event Extraction. Valenzuela-Escarcega, M. A.; Hahn-Powell, G.; Hicks, T.; and Surdeanu, M. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Assian Federation of Natural Language Processing: Software Demonstrations (ACL-IJCNLP), 2015.
A Domain-independent Rule-based Framework for Event Extraction [pdf]Paper   A Domain-independent Rule-based Framework for Event Extraction [link] code   bibtex  
Two Practical Rhetorical Structure Theory Parsers. Surdeanu, M.; Hicks, T.; and Valenzuela-Escarcega, M. A. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT): Software Demonstrations, 2015.
Two Practical Rhetorical Structure Theory Parsers [pdf]Paper   Two Practical Rhetorical Structure Theory Parsers [link] code   bibtex  
Diamonds in the Rough: Event Extraction from Imperfect Microblog Data. Intxaurrondo, A.; Agirre, E.; de Lacalle, O. L.; and Surdeanu, M. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT), 2015.
Diamonds in the Rough: Event Extraction from Imperfect Microblog Data [pdf]Paper   Diamonds in the Rough: Event Extraction from Imperfect Microblog Data [link] data   bibtex  
Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering. Sharp, R.; Jansen, P.; Surdeanu, M.; and Clark, P. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT), 2015.
Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering [pdf]Paper   Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering [link] data and some code   bibtex  
Higher-order Lexical Semantic Models for Non-factoid Answer Reranking. Fried, D.; Jansen, P.; Hahn-Powell, G.; Surdeanu, M.; and Clark, P. Transactions of the Association for Computational Linguistics, 3: 197-210. 2015.
Higher-order Lexical Semantic Models for Non-factoid Answer Reranking [link]Paper   bibtex   abstract  
Description of the odin event extraction framework and rule language. Valenzuela-Escarcega, M. A; Hahn-Powell, G.; and Surdeanu, M. arXiv preprint arXiv:1509.07513. 2015.
Description of the odin event extraction framework and rule language [link]Paper   bibtex  
  2014 (7)
Discourse Complements Lexical Semantics for Non-factoid Answer Reranking. Jansen, P.; Surdeanu, M.; and Clark, P. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL), 2014.
Discourse Complements Lexical Semantics for Non-factoid Answer Reranking [pdf]Paper   Discourse Complements Lexical Semantics for Non-factoid Answer Reranking [link] code and data   Discourse Complements Lexical Semantics for Non-factoid Answer Reranking [link] slides   bibtex  
The Stanford CoreNLP Natural Language Processing Toolkit. Manning, C. D.; Surdeanu, M.; Bauer, J.; Finkel, J.; Bethard, S. J.; and McClosky, D. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL), 2014.
The Stanford CoreNLP Natural Language Processing Toolkit [pdf]Paper   The Stanford CoreNLP Natural Language Processing Toolkit [link] code   bibtex  
Analyzing the Language of Food on Social Media. Fried, D.; Surdeanu, M.; Kobourov, S.; Hingle, M.; and Bell, D. In Proceedings of the 2014 IEEE International Conference on Big Data, 2014.
Analyzing the Language of Food on Social Media [pdf]Paper   Analyzing the Language of Food on Social Media [link] supplmental material   Analyzing the Language of Food on Social Media [link] demo   bibtex  
Overview of the English Slot Filling Track at the TAC2014 Knowledge Base Population Evaluation. Surdeanu, M.; and Heng, J. In Proceedings of the TAC-KBP 2014 Workshop, 2014.
Overview of the English Slot Filling Track at the TAC2014 Knowledge Base Population Evaluation [pdf]Paper   bibtex  
Event Extraction Using Distant Supervision. Reschke, K.; Jankowiak, M.; Surdeanu, M.; Manning, C. D.; and Jurafsky, D. In Proceedings of the 9th edition of the Language Resources and Evaluation Conference (LREC), 2014.
Event Extraction Using Distant Supervision [pdf]Paper   Event Extraction Using Distant Supervision [link] data   Event Extraction Using Distant Supervision [pdf] slides   bibtex  
On the Importance of Text Analysis for Stock Price Prediction. Lee, H.; MacCartney, B.; Surdeanu, M.; and Jurafsky, D. In Proceedings of the 9th edition of the Language Resources and Evaluation Conference (LREC), 2014.
On the Importance of Text Analysis for Stock Price Prediction [pdf]Paper   On the Importance of Text Analysis for Stock Price Prediction [link] data   On the Importance of Text Analysis for Stock Price Prediction [pdf] slides   bibtex  
Extracting Latent Attributes from Video Scenes Using Text as Background Knowledge. Tran, A.; Surdeanu, M.; and Cohen, P. In Proceedings of the Third Joint Conference on Lexical and Computational Semantics (*SEM), 2014.
Extracting Latent Attributes from Video Scenes Using Text as Background Knowledge [pdf]Paper   Extracting Latent Attributes from Video Scenes Using Text as Background Knowledge [pdf] slides   bibtex  
  2013 (7)
Selectional Preferences for Semantic Role Classification. Zapirain, B.; Agirre, E.; Marquez, L.; and Surdeanu, M. Computational Linguistics, 39(3). 2013.
Selectional Preferences for Semantic Role Classification [link]Paper   bibtex  
Deterministic coreference resolution based on entity-centric, precision-ranked rules. Lee, H.; Chang, A.; Peirsman, Y.; Chambers, N.; Surdeanu, M.; and Jurafsky, D. Computational Linguistics, 39(4). 2013.
Deterministic coreference resolution based on entity-centric, precision-ranked rules [link]Paper   bibtex  
Identifying Patent Monetization Entities. Surdeanu, M.; and Jeruss, S. In Proceedings of the XIV International Conference on Artificial Intelligence and Law (ICAIL), 2013.
Identifying Patent Monetization Entities [pdf]Paper   bibtex  
Overview of the TAC2013 Knowledge Base Population Evaluation: English Slot Filling and Temporal Slot Filling. Surdeanu, M. In Proceedings of the TAC-KBP 2013 Workshop, 2013.
Overview of the TAC2013 Knowledge Base Population Evaluation: English Slot Filling and Temporal Slot Filling [pdf]Paper   Overview of the TAC2013 Knowledge Base Population Evaluation: English Slot Filling and Temporal Slot Filling [pdf] slides sf   Overview of the TAC2013 Knowledge Base Population Evaluation: English Slot Filling and Temporal Slot Filling [pdf] slides tsf   bibtex  
Removing Noisy Mentions for Distant Supervision. Intxaurrondo, A.; Surdeanu, M.; de Lacalle, O. L.; and Agirre, E. In Proceedings of the 29th "Congreso de la Sociedad Española para el Procesamiento del Lenguaje Natural" (SEPLN 2013), 2013.
Removing Noisy Mentions for Distant Supervision [pdf]Paper   bibtex  
Transmitting Narrative: An Interactive Shift-Summarization Tool for Improving Nurse Communication. Forbes, A.; Surdeanu, M.; Jansen, P.; and Carrington, J. In Proceedings of the 3rd IEEE Workshop on Interactive Visual Text Analytics, 2013.
Transmitting Narrative: An Interactive Shift-Summarization Tool for Improving Nurse Communication [pdf]Paper   bibtex  
Bayesian modeling of scenes and captions. Colin R. Dawson, L. D. P.; and Barnard, K. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2013), Workshop on Vision and Language (WVL), 2013.
Bayesian modeling of scenes and captions [pdf] slides   bibtex