4CAPS: An Adaptive Architecture for Human Information Processing. - Sashank Varma; Marcel Adam Just (AAAI Spring Symposium: Between a Rock and a Hard Place: Cognitive Science Principles Meet AI-Hard Problems, 2006)

Strangeness. - Sashank Varma; Daniel L. Schwartz; W. Lawrence Neeley Jr. (AAAI Spring Symposium: What Went Wrong and Why: Lessons from AI Research and Applications, 2006)

Is Neuroscience a Learning Science? - Sashank Varma; Daniel L. Schwartz; Bruce D. McCandliss (ICLS, 2006)

Resource Constraints on Computation and Communication in the Brain. - Sashank Varma (IJCAI, 2007)

Criteria for the Design and Evaluation of Cognitive Architectures. - Sashank Varma (Cogn. Sci., 2011)

Integrating Language and Cognitive Architecture. - John Tracy Hale; Richard L. Lewis; David Reitter; Chung-chieh Shan; Sashank Varma (AAAI Fall Symposia, 2013)

Resource-bounded Problem Solving (Dagstuhl Seminar 14341). - Yll Haxhimusa; Iris van Rooij; Sashank Varma; Todd Wareham (Dagstuhl Reports, 2014)

Mental representations and processing of radical expressions. - Purav Patel; Sashank Varma (CogSci, 2016)

The Relationship Between Executive Functions and Science Achievement. - Drake Bauer; Sashank Varma; Keisha Varma; Martin Van Boekel; Alyssa Worley; Jean-Baptiste Quillien; Tayler Loiselle; Purav Patel (CogSci, 2017)

In-Video Reuse of Discussion Threads in MOOCs. - Qian Zhao; Sashank Varma; Joseph A. Konstan (L@S, 2017)

Arithmetic Sense Predicts Children's Mathematical Achievement Better Than Arithmetic Fluency. - Soo-hyun Im; Sashank Varma (CogSci, 2018)

Does shifting ability support interleaved learning of new science concepts in middle school students? - Jimin Park; Keisha Varma; Sashank Varma (CogSci, 2018)

Sequencing Arithmetic, Area, and Algebraic Instruction for Teaching the Distributive Principle. - Soo-hyun Im; Sashank Varma (ICLS, 2018)

How the Abstract Becomes Concrete: Irrational Numbers Are Understood Relative to Natural Numbers and Perfect Squares. - Purav Patel; Sashank Varma (Cogn. Sci., 2018)

Algebra decoded: individual differences in strategy selection when solving for 'x'. - Jeffrey K. Bye; Rina Harsch; Sashank Varma (CogSci, 2020)

Identifying Individual Differences in Sensemaking and Information Foraging. - Kara Kedrick; Sashank Varma; Paul Schrater (CogSci, 2020)

Clustering as a precursor to efficient and near-optimal solution of small instances of the Traveling Salesperson Problem (TSP). - Vijay Marupudi; V. N. Vimal Rao; Jimin Park; Rina Harsch; Jeffrey K. Bye; Sashank Varma (CogSci, 2020)

Calibration information reduces bias during estimation of factorials: A (partial) replication and extension of Tversky and Kahneman (1973). - Jeffrey K. Bye; Vijay Marupudi; Jimin Park; Sashank Varma (CogSci, 2021)

The role of clustering in the efficient solution of small Traveling Salesperson Problems. - Vijay Marupudi; Rina Harsch; V. N. Vimal Rao; Jeffrey K. Bye; Jimin Park; Sashank Varma (CogSci, 2021)

Neighborhood effects for composite (i.e., non-prime) numbers. - Jeffrey K. Bye; Rina Harsch; Sashank Varma (CogSci, 2022)

Learning to count: a neural network model of the successor function. - Vima Gupta; Sashank Varma (CogSci, 2022)

Toward Automated Detection of Phase Changes in Team Collaboration. - Julie L. Harrison; Sona Anita Jain; Terri A. Dunbar; Jamie C. Gorman; Sashank Varma (CogSci, 2022)

Typicality gradients in the category fluency task. - Reba Koenen; Benjamin Y. Hayden; Alexander B. Herman; Sashank Varma (CogSci, 2022)

Catastrophic interference in neural network models is mitigated when the training data reflect a power-law environmental structure. - Sibley F. Lyndgaard; Zachary R. Tidler; Lucas Provine; Sashank Varma (CogSci, 2022)

Use of clustering in human solutions of the traveling salesperson problem. - Vijay Marupudi; Rina Harsch; V. N. Vimal Rao; Jimin Park; Jeffrey K. Bye; Sashank Varma (CogSci, 2022)

Typicality Gradients in Computer Vision Models. - Neha Upadhyay; Kritika Mittal; Sashank Varma (CogSci, 2022)

Re-envisioning a K-12 Early Warning System with School Climate Factors. - Mengchen Su; Lukas A. Olson; Daniel C. Jarratt; Sashank Varma; Joseph A. Konstan; Rebecca J. L. Keller; Bodong Chen (L@S, 2022)

Decoding fact fluency and strategy flexibility in solving one-step algebra problems: An individual differences analysis. - Jeffrey K. Bye; Rina Harsch; Sashank Varma (J. Numer. Cogn., 2022)

Categorical Perception of p-Values. - V. N. Vimal Rao; Jeffrey K. Bye; Sashank Varma (Top. Cogn. Sci., 2022)

Numeric Magnitude Comparison Effects in Large Language Models. - Raj Sanjay Shah; Vijay Marupudi; Reba Koenen; Khushi Bhardwaj; Sashank Varma (ACL (Findings), 2023)

Adaptivity and optimization under constraints. - Reba Koenen; Sashank Varma (CogSci, 2023)

Models of human visual clustering. - Vijay Marupudi; Sashank Varma (CogSci, 2023)

Unifying exemplar and prototype models of categorization. - Max Zuo; Vijay Marupudi; Sashank Varma (CogSci, 2023)

Pre-training LLMs using human-like development data corpus. - Khushi Bhardwaj; Raj Sanjay Shah; Sashank Varma (CoRR, 2023)

Neural Network Models of Becoming a Cardinal Principle Knower. - Vima Gupta; Sashank Varma (CoRR, 2023)

Development of Cognitive Intelligence in Pre-trained Language Models. - Raj Sanjay Shah; Khushi Bhardwaj; Sashank Varma (EMNLP, 2024)

Catastrophic Interference is Mitigated in Naturalistic Power-Law Learning Environments. - Atith Gandhi; Raj Sanjay Shah; Vijay Marupudi; Sashank Varma (CoRR, 2024)

Cobweb: An Incremental and Hierarchical Model of Human-Like Category Learning. - Xin Lian; Sashank Varma; Christopher J. MacLellan (CoRR, 2024)

Towards a Path Dependent Account of Category Fluency. - David Heineman; Reba Koenen; Sashank Varma (CoRR, 2024)

Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attention. - Andrew Li; Xianle Feng; Siddhant Narang; Austin Peng; Tianle Cai; Raj Sanjay Shah; Sashank Varma (CoRR, 2024)

How Well Do Deep Learning Models Capture Human Concepts? The Case of the Typicality Effect. - Siddhartha K. Vemuri; Raj Sanjay Shah; Sashank Varma (CoRR, 2024)

Understanding Graphical Perception in Data Visualization through Zero-shot Prompting of Vision-Language Models. - Grace Guo; Jenna Jiayi Kang; Raj Sanjay Shah; Hanspeter Pfister; Sashank Varma (CoRR, 2024)

Introduction to Progress and Puzzles of Cognitive Science. - Rick Dale; Ruth M. J. Byrne; Emma Cohen; Ophelia Deroy; Samuel J. Gershman; Janet H. Hsiao; Ping Li 026; Padraic Monaghan; David C. Noelle; Iris van Rooij; Priti Shah; Michael J. Spivey; et al. (Cogn. Sci., 2024)

Alignment of CNN and Human Judgments of Geometric and Topological Concepts. - Neha Upadhyay; Vijay Marupudi; Kamala Varma; Sashank Varma (AAAI, 2025)

The potential - and the pitfalls - of using pre-trained language models as cognitive science theories. - Raj Sanjay Shah; Sashank Varma (CoRR, 2025)

Computer Vision Models Show Human-Like Sensitivity to Geometric and Topological Concepts. - Zekun Wang; Sashank Varma (CoRR, 2025)

Modeling Understanding of Story-Based Analogies Using Large Language Models. - Kalit Inani; Keshav Kabra; Vijay Marupudi; Sashank Varma (CoRR, 2025)

A Neural Network Model of Complementary Learning Systems: Pattern Separation and Completion for Continual Learning. - James P. Jun; Vijay Marupudi; Raj Sanjay Shah; Sashank Varma (CoRR, 2025)

The World According to LLMs: How Geographic Origin Influences LLMs' Entity Deduction Capabilities. - Harsh Nishant Lalai; Raj Sanjay Shah; Jiaxin Pei; Sashank Varma; Yi-Chia Wang; Ali Emami (CoRR, 2025)