Papers By Topic

Hen Emuna, Nadav Borenstein, Xin Qian, Hyeonsu Kang, Joel Chan, Aniket Kittur, Dafna Shahaf, Imitation of Life: A Search Engine for Biologically Inspired Design
AAAI'24: The 38th AAAI Conference On Artificial Intelligence

Shahar Jacob, Chen Shani, Dafna Shahaf, FAME: Flexible, Scalable Analogy Mappings Engine
EMNLP'23: The Conference on Empirical Methods in Natural Language Processing

Chen Shani, Jilles Vreeken, Dafna Shahaf, Towards Concept-Aware Large Language Models
Findings of EMNLP 2023

Ron Yosef, Yonatan Bitton, Dafna Shahaf, IRFL: Image Recognition of Figurative Language
Findings of EMNLP 2023

Yonatan Bitton, Ron Yosef, Eliyahu Strugo, Dafna Shahaf, Roy Schwartz, Gabriel Stanovsky, VASR: Visual Analogies of Situation Recognition
AAAI'23: The 37th AAAI Conference On Artificial Intelligence

Oren Sultan and Dafna Shahaf, Life is a Circus and We are the Clowns: Automatically Finding Analogies between Situations and Processes
EMNLP'22: The Conference on Empirical Methods in Natural Language Processing

Kyle Richardson, Ronen Tamari, Oren Sultan, Dafna Shahaf, Reut Tsarfaty and Ashish Sabharwal, Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs
EMNLP'22: The Conference on Empirical Methods in Natural Language Processing

Ronen Tamari, Kyle Richardson, Aviad Sar-Shalom, Noam Kahlon, Nelson Liu, Reut Tsarfaty and Dafna Shahaf, Dyna-bAbI: unlocking bAbI's potential with dynamic synthetic benchmarking
*SEM, 2022

Tom Hope, Ronen Tamari, Daniel Hershcovich, Hyeonsu B Kang, Joel Chan, Aniket Kittur and Dafna Shahaf, Scaling Creative Inspiration with Fine-Grained Functional Aspects of Ideas
CHI, 2022

Hyeonsu B Kang, Xin Qian, Tom Hope, Dafna Shahaf, Joel Chan and Aniket Kittur, Augmenting scientific creativity with an analogical search engine
ACM Transactions on Computer-Human Interaction (TOCHI), 2022

Ronen Tamari, Chen Shani, Tom Hope, Miriam RL Petruck, Omri Abend, and Dafna Shahaf, Language (re)modelling: Towards embodied language understanding
Association for Computational Linguistics (ACL), 2020

Ronen Tamari, Gabriel Stanovsky, Dafna Shahaf, and Reut Tsarfaty, Ecological semantics: Programming environments for situated language understanding
Bridging AI and Cognitive Science (BAICS) at International Conference on Learning Representations (ICLR), 2020

Ronen Tamari, Hiroyuki Shindo, Dafna Shahaf, and Yuji Matsumoto, Playing by the Book: An Interactive Game Approach for Action Graph Extraction from Text
NAACL-HLT workshop on extracting structured knowledge from scientific publications (ESSP), 2019

Aniket Kittur, Lixiu Yu, Tom Hope, Joel Chan, Hila Lifshitz-Assaf, Karni Gilon, Felicia Ng, Robert E. Kraut, and Dafna Shahaf, Scaling Up Analogy-based Innovation with Crowds and AI
PNAS 2019

Joel Chan, Joseph Chee Chang, Tom Hope, Dafna Shahaf, and Aniket Kittur, SOLVENT: A Mixed Initiative System for Finding Analogies between Research Papers
CSCW 2018

Karni Gilon, Felicia Ng, Joel Chan, Dafna Shahaf and Aniket Kittur, Analogy Mining for Specific Design Needs
CHI 2018

Tom Hope, Joel Chan, Aniket Kittur and Dafna Shahaf, Accelerating Innovation Through Analogy Mining
KDD 2017

 Best Research Paper and Best Student Research Paper, KDD'17

Joel Chan, Tom Hope, Dafna Shahaf and Aniket Kittur, Scaling up Analogy with Crowdsourcing and Machine Learning
ICCBR-16 Computational Analogy Workshop

Dan Ofer and Dafna Shahaf, Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game
Findings of EMNLP 2022

Chen Shani, Alexander Libov, Sofia Tolmach, Liane Lewin-Eytan, Yoelle Maarek and Dafna Shahaf, Alexa, Do You Want to Build a Snowman? Characterizing Playful Requests to Conversational Agents
CHI, 2022

Chen Shani, Nadav Borenstein, Dafna Shahaf, How Did This Get Funded?! Automatically Identifying Quirky Scientific Achievements
Association for Computational Linguistics (ACL), 2021

Nir Sweed, Dafna Shahaf, Catchphrase: Automatic Detection of Cultural References
Association for Computational Linguistics (ACL), 2021

David Tsurel, Dan Pelleg, Ido Guy and Dafna Shahaf, Fun Facts: Automatic Trivia Fact Extraction from Wikipedia
WSDM 2017

Dafna Shahaf, A Hard Look at Soft Concepts
IJCAI 2016

 Early Career Award

Dafna Shahaf, Eric Horvitz and Robert Mankoff, Inside Jokes: Identifying Humorous Cartoon Captions
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2015. Also presented at the 2015 International Humor Conference.

We study the influence of the language of cartoon captions on the perceived humorousness of the cartoons. Our studies are based on a large corpus of crowdsourced cartoon captions that were submitted to a contest hosted by the New Yorker.
 Also became a book chapter: The Languages of Humor: Verbal, Visual, and Physical Humor, Bloomsbury Academic, 2018

Yuval Barak-Corren1, David Tsurel, Daphna Keidar, Ilan Gofer, Dafna Shahaf, Maya Leventer-Roberts, Noam Barda, and Ben Y. Reis, The value of parental medical records for the prediction of diabetes and cardiovascular disease: a novel method for generating and incorporating family histories
Journal of the American Medical Informatics Association, 2023

Moran Mizrahi, Guy Kaplan, Dan Malkin, Rotem Dror, Dafna Shahaf, Gabriel Stanovsky, State of what art? a call for multi-prompt llm evaluation
ArXiv preprint

Ronen Tamari, Daniel Friedman, William Fischer, Lauren Hebert and Dafna Shahaf, From Users to (Sense) Makers: On the Pivotal Role of Stigmergic Social Annotation in the Quest for Collective Sensemaking
HT, 2022

Chen Shani, Jonathan Zarecki, Dafna Shahaf, The Lean Data Scientist: Recent Advances towards Overcoming the Data Bottleneck
Communications of the ACM (CACM)

Moran Mizrahi, Stav Yardeni Seelig, Dafna Shahaf, Coming to Terms: Automatic Formation of Neologisms in Hebrew
Findings of the Association for Computational Linguistics (EMNLP), 2020

David Tsurel, Michael Doron, Alexander Nus, Arnon Dagan, Ido Guy, and Dafna Shahaf, E-Commerce Dispute Resolution Prediction
CIKM, 2020

Asaf Valadarsky, Michael Schapira, Dafna Shahaf, and Aviv Tamar, Learning to Route
HotNets, 2017

Tom Hope and Dafna Shahaf, Ballpark Learning: Estimating Labels from Rough Group Comparison

 MIT Tech Review: This week's most thought-provoking papers from the Physics arXiv. (Link)

Dafna Shahaf, Carlos Guestrin, Eric Horvitz, Jure Leskovec, Information Cartography
Communications of the ACM (CACM), 2016

Dafna Shahaf, Jaewon Yang, Caroline Suen, Jeff Jacobs, Heidi Wang and Jure Leskovec, Information Cartography: Creating Zoomable, Large-Scale Maps of Information
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2013

We propose a methodology for creating structured summaries of information, which we call zoomable metro maps. Just as cartographic maps have been relied upon for centuries to help us understand our surroundings, metro maps can help us understand the information landscape. [...] As different users might be interested in different levels of granularity, the maps are zoomable, with each level of zoom showing finer details and interactions.

Dafna Shahaf, Carlos Guestrin and Eric Horvitz, Metro Maps of Information
ACM SIGWEB Newsletter, 2013

Dafna Shahaf, Carlos Guestrin and Eric Horvitz, Metro Maps of Science
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2012

Dafna Shahaf, Carlos Guestrin and Eric Horvitz, Trains of Thought: Generating Information Maps
International World Wide Web Conference (WWW), 2012

Complex stories spaghetti into branches, side stories, and intertwining narratives. In order to explore these stories, one needs a map to navigate unfamiliar territory. We propose a methodology for creating structured summaries of information, which we call metro maps. [...] Most importantly, metro maps explicitly show the relations among retrieved pieces in a way that captures story development.

Dafna Shahaf and Carlos Guestrin, Connecting Two (or Less) Dots: Discovering Structure in News Articles
ACM Transactions on Knowledge Discovery from Data, 2011.

Dafna Shahaf and Carlos Guestrin, Connecting the Dots Between News Articles.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2010. Also presented at IJCAI'11

 Best Research Paper, KDD'10

Khalid El-Arini, Gaurav Veda, Dafna Shahaf, and Carlos Guestrin, Turning Down the Noise in the Blogosphere
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2009

In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information overload. [...] we present a principled approach for picking a set of posts that best covers the important stories in the blogosphere. [...] In addition, since people have varied interests, our coverage algorithm incorporates user preferences in order to tailor the selected posts to individual tastes.

Dafna Shahaf and Eric Horvitz, Generalized task markets for human and machine computation
The Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI) 2010

We discuss challenges and opportunities for developing generalized task markets where human and machine intelligence are enlisted to solve problems, based on a consideration of the competencies, availabilities, and pricing of different problemsolving resources. The approach couples human computation with machine learning and planning, and is aimed at optimizing the flow of subtasks to people and to computational problem solvers. We illustrate key ideas in the context of Lingua Mechanica, a project focused on harnessing human and machine translation skills to perform translation among languages.
 3rd most-cited paper of AAAI'10 (@2014)

Dafna Shahaf and Eyal Amir, Towards a Theory of AI-Completeness
CommonSense 2007

(A thought experiment: complexity models for computational problems that include a human in the process. Take with a grain of salt)

Yossi Azar, Eric Horvitz, Eyal Lubetzky, Yuval Peres, and Dafna Shahaf, Tractable near-optimal policies for crawling
PNAS, 2018