Publications

THESES & TECHNICAL REPORTS

Scott Friedman. (2012). Computational Conceptual Change: An Explanation-Based Approach. Doctoral Dissertation. Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois.

Scott Friedman. (2005). Dusty Caches to Save Memory Traffic. Thesis for Master of Science in Computer Science. Washington University in St. Louis, MO.

PATENTS

Ian H. Magnusson, Scott Ehrlich Friedman, Sonja M. Schmer-Galunder. (2023).  Machine learning for joint recognition and assertion regression of elements in text.  U.S. Patent No. 11,755,838 B2.

Scott Ehrlich Friedman, Robert Prescott Goldman, Richard Gabriel Freedman, Ugur Kuter, Christopher William Geib, Jeffrey M. Rye. (2022). Machine architecture for computerized plan analysis with provenance. U.S. Patent No. 11,468,608 B2.

Scott Ehrlich Friedman, Jeffrey Mathew Rye, David Thomas LaVergne. (2021). Provenance analysis systems and methods. U.S. Patent No. 11,372,854 B2.

Scott E. Friedman, David J. Musliner, Peter K. Keller (2020).  Methods and systems for defending against cyber-attacks (Continuation). U.S. Patent  No. 10/528,729.

Scott E. Friedman, David J. Musliner, Peter K. Keller (2018).  Methods and systems for defending against cyber-attacks. U.S. Patent No. 10/108,798.

BOOK CHAPTERS & MAGAZINE ARTICLES

Scott E. Friedman and Micah Goldwater. (2022). Computational modeling of representational pluralism in explanations. In Multidisciplinary Perspectives on Representational Pluralism in Human Cognition (pp. 81-103). Routledge.

Scott E. Friedman, Kate Lockwood (2016). Qualitative Reasoning: Everyday, Pervasive, and Moving Forward - A Report on QR-15. AI Magazine, 37(2). pp. 95-96.

JOURNAL & MAGAZINE ARTICLES

Nathan Brugnone, Noam Benkler, Peter Revay, Rebecca Myhre, Scott Friedman, Sonja Schmer-Galunder, Steven Gray, and James Gentile.  (2024). Is from ought? A comparison of unsupervised methods for structuring values-based wisdom-of-crowds estimates. Journal of Computational Social Science: 1-51.

Sonja Schmer-Galunder, Ruta Wheelock, Joan Zheng, Claire Yang, Ian Magnusson, Jeremy Gottlieb, Scott Friedman and Nathaniel Budijono. (accepted). Linguistic Factors in Incel Messaging. Special Issue for the Workshop on Online Abuse and Harm.

Mark Burstein, Scott Friedman, David McDonald, Jeffrey Rye, Alex Plotnick, Laurel Bobrow, Robert Bobrow. (2020). Using multiple contexts to interpret collaborative task dialogs. Advances in Cognitive Systems, 9, 71-90.

Scott E. Friedman, Kenneth Forbus, and Bruce Sherin (2018). Representing, Running, and Revising Mental Models: A Computational Model. Cognitive Science, 42(4): 1110-1145. doi:10.1111/cogs.12574

Scott E. Friedman, Mark Burstein, David McDonald, Alex Plotnick, Laurel Bobrow, Rusty Bobrow, Brent Cochran, James Pustejovsky (2017). Learning by Reading: Extending and Localizing Against a Model. Advances in Cognitive Systems, 5, pp. 77-96.

David J. Musliner, Scott E. Friedman, Michael Boldt, J. Benton, Max Schuchard, Peter K. Keller, and Stephen McCamant. (2016). FuzzBomb: Fully-Autonomous Detection and Repair of Cyber Vulnerabilities. International Journal on Advances in Security, 9(3&4). pp. 111-121.

Scott E. Friedman, David J. Musliner, Peter K. Keller. (2015). Chronomorphic Programs: Runtime Diversity Prevents Exploits and Reconnaissance. International Journal on Advances in Security, 8(3&4). pp. 120-129.

Scott E. Friedman, David J. Musliner, Jeffrey M. Rye. (2014). Improving Automated Cybersecurity by Generalizing Faults and Quantifying Patch Performance. International Journal on Advances in Security, 7(3&4). pp. 121-130.

Scott E. Friedman, David M. Barbella, Kenneth D. Forbus. (2012). Revising Domain Knowledge with Cross-Domain Analogy. Advances in Cognitive Systems, 2: 13-24.

Sara Friedman, Benjamin Sayers, Matt Lazio, Scott Friedman, Michael Gisondi (2010). Curriculum Design of a Case-Based Knowledge Translation Shift for Emergency Medicine Residents. Academic Emergency Medicine, 17(s2). 42-48.

Shobana Padmanabhan, Phillip Jones, David V. Schuehler, Scott Friedman, Praveen Krishnamurthy, Huakai Zhang, Roger Chamberlain, Ron K. Cytron, Jason Fritts, and John W. Lockwood. (2005). Extracting and Improving Microarchitecture Performance on Reconfigurable Architectures. International Journal of Parallel Programming, 33(2). 115 - 136.

REFEREED CONFERENCES

Scott Friedman, Joan Zheng, and Hillel Steinmetz. (2024). Debiasing Multi-Entity Aspect-Based Sentiment Analysis with Norm-Based Data Augmentation.  COLING-LREC 2024.

Noam K. Benkler, Scott Friedman, Sonja Schmer-Galunder, Drisana Marissa Mosaphir, Robert P. Goldman, Ruta Wheelock, Vasanth Sarathy, Pavan Kantharaju and Matthew D. McLure. (2024). Recognizing Value Resonance with Resonance-Tuned RoBERTa Task Definition, Experimental Validation, and Robust Modeling. COLING-LREC 2024.

Scott Friedman, Sonja Schmer-Galunder, Vasanth Sarathy, Ruta Wheelock, Matthew McLure, Drisana M. Mosaphir, Robert P. Goldman, Noam Benkler, Pavan Kantharaju, Micah B. Goldwater, and Cristine H. Legare. (2023). Mapping a Plurality of Explanations with NLP: A Case Study of Mothers and Health Workers in India. CogSci 2023.

Sara Friedman, Scott Friedman, Abbey Sidebottom, Bailey Van Eyll, and Sean Boley.  (2023). Toward a Real-Time AI Assistant for Characterizing and Mitigating Language Bias in Emergency Medicine Notes   American College of Emergency Physicians (ACEP).

Noam Benkler, Scott Friedman, Sonja Schmer-Galunder, Drisana Mosaphir, Vasanth Sarathy, Pavan Kantharaju, Matthew McLure and Robert Goldman. (2022). Cultural Value Resonance in Folktales: A Transformer-based Analysis with the World Value Corpus. SBP-BRiMS 2022.

Vasanth Sarathy, Mark Burstein, Scott Friedman, Robert Bobrow and Ugur Kuter. (2022). A Neuro-Symbolic Cognitive System for Intuitive Argumentation. Advances in Cognitive Systems 2022.

Scott E. Friedman, Ian H. Magnusson, Vasanth Sarathy, and Sonja M. Schmer-Galunder. (2021). From Unstructured Text to Causal Knowledge Graphs: A Transformer-Based Approach. Advances in Cognitive Systems 2021.

Ian H. Magnusson and Scott E. Friedman. (2021). Extracting Fine-Grained Knowledge Graphs of Scientific Claims: Dataset and Transformer-Based Results.  Empirical Methods in Natural Language Processing (EMNLP).

Scott Friedman, Jeffrey Rye, Matthew McLure, Helen Wauck, Pooja Patel, Ruta Wheelock, Mark Valovage, Steven Johnston, and Christopher Miller. (2021). Provenance as a Substrate for Human Sensemaking and Explanation of Machine Collaborators. IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Scott E. Friedman, Ian H. Magnusson, Sonja M. Schmer-Galunder, Ruta Wheelock, Jeremy Gottlieb,  Pooja Patel, and Christopher Miller. (2021). Toward Transformer-Based NLP for Extracting  Psychosocial Indicators of Moral Disengagement. CogSci 2021.

Alipourfard, Nazanin, Beatrix Arendt, Daniel M. Benjamin, Noam Benkler, Michael M. Bishop, Mark Burstein, Martin Bush, et al. (2021). Systematizing Confidence in Open Research and Evidence (SCORE). SocArXiv. May 4. doi:10.31235/osf.io/46mnb.

Scott Friedman, Jeffrey Rye, David LaVergne, Dan Thomsen, Matthew Allen, and Kyle Tunis. (2020). Provenance-Based Interpretation of Multi-Agent Information Analysis. TaPP 2020. Charlotte, NC.

Scott Friedman, Sonja Schmer-Galunder, Anthony Chen, Robert Goldman, and Michelle Ausman. (2020). Gender Gaps Correlate with Gender Bias in Social Media Word Embeddings. CogSci 2020. Toronto, CA.

Nikhil Krishnaswamy, Scott Friedman, James Pustejovsky. (2019). Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise. AAAI 2019. Honolulu, HI.

Mark Burstein, David McDonald, Scott Friedman, Jeffrey Rye, Robert Bobrow, Alex Plotnick and Laurel Bobrow. (2019). Using Multiple Contexts to Interpret Collaborative Task Dialogs. Advances in Cognitive Systems 2019. Boston, MA.

Scott Friedman, Sonja Schmer-Galunder, Jeffrey Rye, Robert Goldman, and Anthony Chen. (2019). Relating Linguistic Gender Bias, Gender Values, and Gender Gaps: An International Analysis. SBP-BRiMS 2019. Washington, DC.

Scott Friedman and Micah Goldwater. (2019). Simulating Explanatory Coexistence: Integrated, Synthetic, and Target-Dependent Reasoning. CogSci 2019. Montral, Canada.

Ian Perera, James Allen, Lucian Galescu, Choh Man Teng, Mark Burstein, Scott Friedman, David McDonald, and Jeffrey Rye. (2017). Natural Language Dialogue for Building and Learning Models and Structures. AAAI 2017, demo track. San Francisco, CA.

Scott E. Friedman. (2016). Exploiting Graph Structure to Abstract & Compress Relational Data. Proceedings of the 4th Annual Conference on Advances in Cognitive Systems.  Evanston, IL.

Scott E. Friedman, Mark Burstein, David McDonald, Amandalynne Paullada, Alex Plotnick, Rusty Bobrow, Brent Cochran, James Pustejovsky, Peter Anick. (2016). Learning By Reading: Extending & Localizing Against a Model. Proceedings of the 4th Annual Conference on Advances in Cognitive Systems.  Evanston, IL.

Matthew D. McLure, Scott E. Friedman,  Kenneth D. Forbus. (2015). Extending Analogical Generalization with Near-Misses. Proceedings of the 29th AAAI Conference on Artificial Intelligence. Austin, TX.

Scott E. Friedman, David J. Musliner, Peter Keller. (2015). Chronomorphic Programs: Using Runtime Diversity to Prevent Code Reuse Attacks. ICDS 2015: The 9th International Conference on Digital Society.

David J. Musliner, Scott E. Friedman, Michael Boldt, J. Benton, Max Schuchard, Peter Keller, Stephen McCamant. (2015). FuzzBOMB: Autonomous Cyber Vulnerability Detection and Repair. INNOV 2015: The Fourth International Conference on Communications, Computation, Networks and Technologies. Best Paper Award.

David J. Musliner, Scott E. Friedman, Jeffrey M. Rye. (2014). Automated Fault Analysis and Filter Generation for Adaptive Cybersecurity. ADAPTIVE 2014 : The Sixth International Conference on Adaptive and Self-Adaptive Systems and Applications. Venice, Italy. Best Paper Award.

David J. Musliner, Scott E. Friedman, Jeffrey M. Rye, Tom Marble. (2013). Meta-control for Adaptative Cybersecurity in FUZZBUSTER. Proceedings of SASO 2013. Philadelphia, PA.

Scott E. Friedman, Kenneth D. Forbus. (2011). Repairing Incorrect Knowledge with Model Formulation and Metareasoning. Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI). Barcelona, Spain.

Jason L. M. Taylor, Scott E. Friedman, Kenneth Forbus, Micah Goldwater, Dedre Gentner. (2011). Modeling structural priming in sentence production via analogical processes. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Boston, MA.

Scott E. Friedman, Kenneth D. Forbus. (2010). An integrated systems approach to explanation-based conceptual change. Proceedings of the 25th AAAI Conference on Artificial Intelligence. Atlanta, GA.

Matthew McLure, Scott E. Friedman, Kenneth D. Forbus. (2010). Learning concepts from sketches via analogical generalization and near-misses. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

Scott E. Friedman, Jason Taylor, Kenneth D. Forbus. (2009). Learning Naive Physics Models by Analogical Generalization. Proceedings of the 2nd International Analogy Conference. Sofia, Bulgaria.

Jana Zujovic, Lisa Gandy, Scott Friedman, Bryan Pardo, Thrasyvoulos Pappas. (2009). Classifying Paintings by Artistic Genre: An Analysis of Features & Classifiers. Proceedings of Multimedia Signal Processing (MMSP). Rio de Janiero, Brazil.

Scott E. Friedman, Kenneth D. Forbus. (2009). Learning Naive Physics Models & Misconceptions. Proceedings of the 31st Annual Conference of the Cognitive Science Society. Amsterdam, Netherlands.

Scott E. Friedman, Kenneth D. Forbus. (2008). Learning Causal Models via Progressive Alignment & Qualitative Modeling: A Simulation. Proceedings of the 30th Annual Conference of the Cognitive Science Society. Washington, D.C.

REFEREED WORKSHOPS & SYMPOSIA

Noam Benkler, Drisana Mosaphir, Scott E. Friedman, Andrew J Smart, Sonja M. Schmer-Galunder. (2023). Assessing LLMs for Moral Value Pluralism. MP2 @ NeurIPS 2023.

Joan Zheng, Scott Friedman, Sonja Schmer-Galunder, Ian Magnusson, Ruta Wheelock, Jeremy Gottlieb, Diana Gomez, and Chris Miller. (2022). Towards a Multi-Entity Aspect-Based Sentiment Analysis for Characterizing Directed Social Regard in Online Messaging. NAACL Workshop on Online Abuse and Harms, 2022 .

Scott E. Friedman, Ian H. Magnusson, and Sonja M. Schmer-Galunder (2021). Extracting Qualitative Causal Structure with Transformer-Based NLP.  IJCAI Workshop on Qualitative Reasoning.

Ian H. Magnusson and Scott E. Friedman. (2021). Graph Knowledge Extraction of Causal, Comparative, Predictive, and Proportional Associations in Scientific Claims with a Transformer-Based Model.  AAAI Workshop on Scientific Document Understanding.

Ben Gelman, Chae Clark, Scott E. Friedman, Ugur Kuter, and James Gentile (2021). Toward A Robust Method for Understanding the Replicability of Research.  AAAI Workshop on Scientific Document Understanding.

Scott Friedman, Robert P. Goldman, Richard G. Freedman, Ugur Kuter, Christopher Geib, and Jeffrey Rye (2020). Provenance-Based Interpretation of Plans in Context. ICAPS Workshop on Explainable AI Planning.

Richard Freedman, Scott Friedman, Michael Pelican, and David Musliner. (2020). Creative Problem Solving Through Automated Planning and Analogy. AAAI-20 workshop on Generalization in Planning.  New York, NY.

Scott Friedman, Sonja Schmer-Galunder, Anthony Chen, and Jeffrey Rye. (2019). Relating Word Embedding Gender Biases to Gender Gaps: A Cross-Cultural Analysis. ACL Workshop on Gender Bias in NLP. Florence, Italy.

Robert P. Goldman, Scott E. Friedman, and Jeffrey M. Rye. (2018). Plan Recognition for Network Analysis: Preliminary Report. AAAI Workshop on Plan, Activity and Intent Recognition. New Orleans, LA.

Scott E. Friedman, Mark H. Burstein, Jeffrey M. Rye, and Ugur Kuter. (2017). Analogical Localization: Flexible Plan Execution in Open Worlds. ICCBR Computational Analogy Workshop. Trondheim, Norway.

Scott E. Friedman, Mark Burstein, David McDonald, Roger Rosewall, and J. Benton (2016). STRIDER: Toward an AI Collaborator for Intelligence Analysis.  Proceedings of the IJCAI Cognitive Computation Workshop. New York, NY.

Scott E. Friedman, Mark Burstein, David McDonald, James Pustejovsky, Peter Anick, Rusty Bobrow, Brent Cochran. (2016). Reconciling Function and Structure in Scientific Models. Proceedings of the 29th International Workshop on Qualitative Reasoning.  New York, NY.

David McDonald, Scott E. Friedman, Amandalynne Paullada, Rusty Bobrow, Mark Burstein. (2016). Extending Biology Models with Deep NLP over Scientific Articles. AAAI-16 Workshop on Knowledge Extraction from Text. Phoenix, AZ.

Scott E. Friedman, David J. Musliner. (2015). Automatically Repairing Stripped Executables with CFG Microsurgery. Fourth annual SASO workshop on Adaptive Host and Network Security. Boston, MA.

Scott E. Friedman. (2015). Exploiting Graph Structure to Summarize and Compress Relational Knowledge. Proceedings of the 28th International Workshop on Qualitative Reasoning.  Minneapolis, MN.

Scott E. Friedman, J. Benton, Dan Bryce. (2015). Toward Automatic Ontology Curation with Similarity-Based Reasoning. Proceedings of the 28th International Workshop on Qualitative Reasoning.  Minneapolis, MN.

David J. Musliner, Scott E. Friedman, Tom Marble, Jeffrey M. Rye, Michael W. Boldt, Michael Pelican. (2013). Self-Adaptation Metrics for Active Cybersecurity. Second annual SASO workshop on Adaptive Host and Network Security. Philadelphia, PA.

Brett Benyo, Partha Pal, Richard Schantz, Aaron Paulos, David J. Musliner, Tom Marble, Jeffrey M. Rye, Michael W. Boldt, Scott E. Friedman. (2013). Automated Self-Adaptation for Cyber-Defense - Pushing Adaptive Perimter Protection Inward. Second annual SASO workshop on Adaptive Host and Network Security. Philadelphia, PA.

Scott E. Friedman, David M. Barbella, Kenneth D. Forbus. (2012). Repairing Qualitative Domain Knowledge with Cross-Domain Analogy. Proceedings of the 26th International Workshop on Qualitative Reasoning.  Los Angeles, CA.

Scott E. Friedman, Kenneth D. Forbus, Bruce Sherin. (2011). Constructing and revising commonsense science explanations: A metareasoning approach. Proceedings of the AAAI Fall Symposium on Advances in Cognitive Systems.

Scott E. Friedman, Kenneth D. Forbus, Bruce Sherin. (2011). How do the seasons change? Creating & revising explanations via model formulation & metareasoning. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Matthew McLure, Scott E. Friedman, Andrew Lovett, Kenneth D. Forbus. (2011). Edge-cycles: A qualitative sketch representation to support recognition. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Matthew McLure, Scott E. Friedman, Kenneth D. Forbus. (2010). Combining progressive alignment and near-misses to learn concepts from sketches. Proceedings of the 24th International Workshop on Qualitative Reasoning. Portland, OR.

Scott E. Friedman, Kenneth D. Forbus, Jason Taylor. (2009). Learning and Reasoning with Qualitative Models of Physical Behavior. Proceedings of the 23rd International Workshop on Qualitative Reasoning. Ljubljana, Slovenia.

Scott E. Friedman, Kenneth D. Forbus. (2008). Learning Qualitative Causal Models via Generalization & Quantity Analysis. Proceedings of the 22nd International Workshop on Qualitative Reasoning. Boulder, CO.

Matthew Klenk, Scott E. Friedman, Kenneth D. Forbus. (2008). Learning Modeling Abstractions via Generalization. Proceedings of the 22nd International Workshop on Qualitative Reasoning. Boulder, CO.

Richard Hough, Phillip Jones, Scott Friedman, Roger Chamberlain, Jason Fritts, John Lockwood, Ron Cytron. (2006). Cycle-Accurate Microarchitecture Performance Evaluation. IEEE Workshop on Introspective Architecture (WISA). Presentation.

Scott Friedman, Praveen Krishnamurthy, Roger D. Chamberlain, Ron K. Cytron, and Jason E. Fritts. (2005). Dusty Caches for Reference Counting Garbage Collection. MEDEA Workshop. Presentation.

Scott Friedman, John Lockwood, Ron Cytron, Roger Chamberlain, and Jason Fritts. (2005). Dusty Caches for Reducing Reference-Counting Memory Traffic. IEEE Workshop: Architecture Research using FPGA Platforms (WARFP), HPCA11 Conference.

David V. Schuehler, Benjamin C. Brodie, Roger D. Chamberlain, Ron K. Cytron, Scott J. Friedman, Jason Fritts, Phillip Jones, Praveen Krishnamurthy, John W. Lockwood, Shobana Padmanabhan, and Huakai Zhang. (2004). Microarchitecture Optimization for Embedded Systems presentation. High Performance Embedded Computing (HPEC8) Workshop. Presentation.

Shobana Padmanabhan, Phillip Jones, David V. Schuehler, Scott J. Friedman, Praveen Krishnamurthy, Huakai Zhang, Roger Chamberlain, Ron K. Cytron, Jason Fritts, and John W. Lockwood. (2004). Extracting and Improving Microarchitecture Performance on Reconfigurable Architectures. CASES CTCES Workshop.

Scott Friedman, Nicholas Leidenfrost, Benjamin C. Brodie, and Ron K. Cytron. (2001). Hashtables for Embedded and Real-Time Systems. IEEE Real-Time Embedded Systems (RTES) Workshop.

INVITED TALKS

Scott Friedman. (2023). Provenance for Integrity and Transparency in Human-Machine Intelligence Analysis.  NATO Human Factors Panel on Meaningful Human Control.

Scott Friedman and Christopher Miller. (2020). Accounting for Integrity and Cognitive Factors in a Workspace for Human-Machine Team Intelligence Analysis. Department of Defense Human Factors Engineering Technology Advisory Group (DoD HFE TAG).

Scott Friedman. (2018). Hanse-Wissenschaftskolleg (HWK) Study Group on "Modeling Conceptual Knowledge and Conceptual Change" Conference.  Delmenhorst, Germany.

Scott Friedman. (2017). Detecting and summarizing broad relational patterns by analogically generalizing over paths and cycles in relational graphs. Fourth International Analogy Conference.  Paris, France.

REFEREED ABSTRACTS

Xue Zhang, Mark Burstein, Scott Friedman, Jeffrey Rye, and Brent H. Cochran (2020).  A natural language system for analyzing gene regulation. ISMB 2020.

Scott Friedman, Mark Burstein. (2017). Where are we? Localizing within plans and models via structure-mapping. Fourth International Analogy Conference.  Paris, France.

Micah Goldwater, Scott Friedman, Dedre Gentner, Ken Forbus, Jason Taylor. (2011). An Analogical Learning Model of the Development of Thematic Roles & Structural Priming. Boston University Conference on Language Development (BUCLD).