Automated Consistency and Completeness Checking of Testing Models for Interactive Systems. - Amit M. Paradkar; Tim Klinger (COMPSAC, 2004)

Automated Risk Assessment for Managing Software Projects. - Bonnie K. Ray; Tim Klinger; R. Delmonico; Peter Santhanam (SEKE, 2004)

Toward Engineered, Useful Use Cases. - Clay Williams; Matthew Kaplan 003; Tim Klinger; Amit M. Paradkar (J. Object Technol., 2005)

Integrated solution engineering. - Leiguang Gong; Tim Klinger; Paul Matchen; Peri L. Tarr; Rosario Uceda-Sosa; Annie T. T. Ying; Jian Xu; Xin Zhou (OOPSLA Companion, 2006)

Enacting responsibility assignment in software development environments. - Avi Yaeli; Tim Klinger (SDG@ICSE, 2008)

Less is More: A Minimalistic Approach to UML Model-Based Conformance Test Generation. - Matthew Kaplan 003; Tim Klinger; Amit M. Paradkar; Avik Sinha; Clay Williams; Cemal Yilmaz 001 (ICST, 2008)

Roles, rights, and responsibilities: Better governance through decision rights automation. - Alexander Kofman; Avi Yaeli; Tim Klinger; Peri L. Tarr (SDG@ICSE, 2009)

Supporting enterprise stakeholders in software projects. - Clay Williams; Patrick Wagstrom; Kate Ehrlich; Dick Gabriel; Tim Klinger; Jacquelyn Martino; Peri L. Tarr (CHASE, 2010)

An enterprise perspective on technical debt. - Tim Klinger; Peri L. Tarr; Patrick Wagstrom; Clay Williams (MTD@ICSE, 2011)

Inferring developer expertise through defect analysis. - Tung Thanh Nguyen; Tien N. Nguyen; Evelyn Duesterwald; Tim Klinger; Peter Santhanam (ICSE, 2012)

Characterizing defect trends in software support. - Tung Thanh Nguyen; Evelyn Duesterwald; Tim Klinger; Peter Santhanam; Tien N. Nguyen (ICSE Companion, 2014)

Towards Cognitive Automation of Data Science. - Alain Biem; Maria Butrico; Mark Feblowitz; Tim Klinger; Yuri Malitsky; Kenney Ng; Adam Perer; Chandra Reddy; Anton Riabov; Horst Samulowitz; Daby M. Sow; Gerald Tesauro; et al. (AAAI, 2015)

Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation. - Iulian Vlad Serban; Tim Klinger; Gerald Tesauro; Kartik Talamadupula; Bowen Zhou 002; Yoshua Bengio; Aaron C. Courville (AAAI, 2017)

Learning to Query, Reason, and Answer Questions On Ambiguous Texts. - Xiaoxiao Guo; Tim Klinger; Clemens Rosenbaum; Joseph P. Bigus; Murray Campbell; Ban Kawas; Kartik Talamadupula; Gerry Tesauro; Satinder Singh 001 (ICLR (Poster), 2017)

e-QRAQ: A Multi-turn Reasoning Dataset and Simulator with Explanations. - Clemens Rosenbaum; Tian Gao; Tim Klinger (CoRR, 2017)

R3: Reinforced Reader-Ranker for Open-Domain Question Answering. - Shuohang Wang; Mo Yu; Xiaoxiao Guo; Zhiguo Wang; Tim Klinger; Wei Zhang 057; Shiyu Chang; Gerald Tesauro; Bowen Zhou 002; Jing Jiang 001 (CoRR, 2017)

Generation and Consolidation of Recollections for Efficient Deep Lifelong Learning. - Matthew Riemer; Michele Franceschini; Tim Klinger (CoRR, 2017)

R3: Reinforced Ranker-Reader for Open-Domain Question Answering. - Shuohang Wang; Mo Yu; Xiaoxiao Guo; Zhiguo Wang; Tim Klinger; Wei Zhang 057; Shiyu Chang; Gerry Tesauro; Bowen Zhou 002; Jing Jiang 001 (AAAI, 2018)

Routing Networks: Adaptive Selection of Non-Linear Functions for Multi-Task Learning. - Clemens Rosenbaum; Tim Klinger; Matthew Riemer (ICLR (Poster), 2018)

Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering. - Shuohang Wang; Mo Yu; Jing Jiang 001; Wei Zhang 057; Xiaoxiao Guo; Shiyu Chang; Zhiguo Wang; Tim Klinger; Gerald Tesauro; Murray Campbell (ICLR (Poster), 2018)

Logical Rule Induction and Theory Learning Using Neural Theorem Proving. - Andres Campero; Aldo Pareja; Tim Klinger; Josh Tenenbaum 001; Sebastian Riedel 001 (CoRR, 2018)

Scalable Recollections for Continual Lifelong Learning. - Matthew Riemer; Tim Klinger; Djallel Bouneffouf 001; Michele Franceschini (AAAI, 2019)

Recursive Routing Networks: Learning to Compose Modules for Language Understanding. - Ignacio Cases; Clemens Rosenbaum; Matthew Riemer; Atticus Geiger; Tim Klinger; Alex Tamkin; Olivia Li; Sandhini Agarwal; Joshua D. Greene; Dan Jurafsky; Christopher Potts; Lauri Karttunen (NAACL-HLT (1), 2019)

Routing Networks and the Challenges of Modular and Compositional Computation. - Clemens Rosenbaum; Ignacio Cases; Matthew Riemer; Tim Klinger (CoRR, 2019)

Finding Macro-Actions with Disentangled Effects for Efficient Planning with the Goal-Count Heuristic. - Cameron Allen; Tim Klinger; George Konidaris 001; Matthew Riemer; Gerald Tesauro (CoRR, 2020)

A Study of Compositional Generalization in Neural Models. - Tim Klinger; Dhaval Adjodah; Vincent Marois; Josh Joseph; Matthew Riemer; Alex 'Sandy' Pentland; Murray Campbell (CoRR, 2020)

Deep RL With Information Constrained Policies: Generalization in Continuous Control. - Tyler Malloy; Chris R. Sims; Tim Klinger; Miao Liu 001; Matthew Riemer; Gerald Tesauro (CoRR, 2020)

Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games. - Tyler Malloy; Tim Klinger; Miao Liu 001; Matthew Riemer; Gerald Tesauro; Chris R. Sims (CoRR, 2020)

RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract). - Tyler Malloy; Tim Klinger; Miao Liu 001; Gerald Tesauro; Matthew Riemer; Chris R. Sims (AAAI, 2021)

Capacity-Limited Decentralized Actor-Critic for Multi-Agent Games. - Tyler Malloy; Chris R. Sims; Tim Klinger; Miao Liu 001; Matthew Riemer; Gerald Tesauro (CoG, 2021)

Modeling Capacity-Limited Decision Making Using a Variational Autoencoder. - Tyler Malloy; Tim Klinger; Miao Liu 001; Gerald Tesauro; Matthew Riemer; Chris R. Sims (CogSci, 2021)

Efficient Black-Box Planning Using Macro-Actions with Focused Effects. - Cameron Allen; Michael Katz 001; Tim Klinger; George Konidaris 001; Matthew Riemer; Gerald Tesauro (IJCAI, 2021)

Compositional generalization through abstract representations in human and artificial neural networks. - Takuya Ito; Tim Klinger; Douglas Schultz; John Murray; Michael W. Cole; Mattia Rigotti (NeurIPS, 2022)

AI Planning Annotation for Sample Efficient Reinforcement Learning. - Junkyu Lee 001; Michael Katz 001; Don Joven Agravante; Miao Liu 001; Tim Klinger; Murray Campbell; Shirin Sohrabi; Gerald Tesauro (CoRR, 2022)

Laziness Is a Virtue When It Comes to Compositionality in Neural Semantic Parsing. - Maxwell Crouse; Pavan Kapanipathi; Subhajit Chaudhury; Tahira Naseem; Ramón Fernandez Astudillo; Achille Fokoue; Tim Klinger (ACL (1), 2023)

Learning in Factored Domains with Information-Constrained Visual Representations. - Tyler Malloy; Miao Liu 001; Matthew D. Riemer; Tim Klinger; Gerald Tesauro; Chris R. Sims (CoRR, 2023)

Compositional Program Generation for Systematic Generalization. - Tim Klinger; Luke Liu; Soham Dan; Maxwell Crouse; Parikshit Ram; Alexander Gray 001 (CoRR, 2023)

EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning. - Kinjal Basu 002; Keerthiram Murugesan; Subhajit Chaudhury; Murray Campbell; Kartik Talamadupula; Tim Klinger (EACL (1), 2024)

What Makes Models Compositional? A Theoretical View. - Parikshit Ram; Tim Klinger; Alexander G. Gray (IJCAI, 2024)

What makes Models Compositional? A Neuro-Symbolic Theoretical View (Extended Abstract). - Parikshit Ram; Tim Klinger; Alexander G. Gray (LNSAI@IJCAI, 2024)

What makes Models Compositional? A Theoretical View: With Supplement. - Parikshit Ram; Tim Klinger; Alexander G. Gray (CoRR, 2024)

The Importance of Positional Encoding Initialization in Transformers for Relational Reasoning. - Takuya Ito; Luca Cocchi; Tim Klinger; Parikshit Ram; Murray Campbell; Luke J. Hearne (CoRR, 2024)

Quantifying artificial intelligence through algebraic generalization. - Takuya Ito; Murray Campbell; Lior Horesh; Tim Klinger; Parikshit Ram (CoRR, 2024)

Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations. - Stephen Carrow; Kyle Erwin; Olga Vilenskaia; Parikshit Ram; Tim Klinger; Naweed Khan; Ndivhuwo Makondo; Alexander G. Gray (AAAI, 2025)

Transformers Learn Faster with Semantic Focus. - Parikshit Ram; Kenneth L. Clarkson; Tim Klinger; Shashanka Ubaru; Alexander G. Gray (CoRR, 2025)