Attention Word Embedding. - Shashank Sonkar; Andrew E. Waters; Richard G. Baraniuk (COLING, 2020)

qDKT: Question-centric Deep Knowledge Tracing. - Shashank Sonkar; Andrew S. Lan; Andrew E. Waters; Phillip Grimaldi; Richard G. Baraniuk (EDM, 2020)

NePTuNe: Neural Powered Tucker Networkfor Knowledge Graph Completion. - Shashank Sonkar; Arzoo Katiyar; Richard G. Baraniuk (IJCKG, 2021)

NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion. - Shashank Sonkar; Arzoo Katiyar; Richard G. Baraniuk (CoRR, 2021)

A Visual Tour Of Current Challenges In Multimodal Language Models. - Shashank Sonkar; Naiming Liu; Richard G. Baraniuk (CoRR, 2022)

Deduction under Perturbed Evidence: Probing Student Simulation (Knowledge Tracing) Capabilities of Large Language Models. - Shashank Sonkar; Richard G. Baraniuk (LLM@AIED, 2023)

CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles. - Shashank Sonkar; Naiming Liu; Debshila Basu Mallick; Richard G. Baraniuk (EMNLP (Findings), 2023)

MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages. - Shashank Sonkar; Zichao Wang 001; Richard G. Baraniuk (SustaiNLP, 2023)

CLASS Meet SPOCK: An Education Tutoring Chatbot based on Learning Science Principles. - Shashank Sonkar; Lucy Liu; Debshila Basu Mallick; Richard G. Baraniuk (CoRR, 2023)

Investigating the Role of Feed-Forward Networks in Transformers Using Parallel Attention and Feed-Forward Net Design. - Shashank Sonkar; Richard G. Baraniuk (CoRR, 2023)

Deduction under Perturbed Evidence: Probing Student Simulation Capabilities of Large Language Models. - Shashank Sonkar; Richard G. Baraniuk (CoRR, 2023)

Novice Learner and Expert Tutor: Evaluating Math Reasoning Abilities of Large Language Models with Misconceptions. - Naiming Liu; Shashank Sonkar; Zichao Wang 001; Simon Woodhead 002; Richard G. Baraniuk (CoRR, 2023)

Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. - Shashank Sonkar; Naiming Liu; Debshila Basu Mallick; Richard G. Baraniuk (AIED (1), 2024)

Automated Long Answer Grading with RiceChem Dataset. - Shashank Sonkar; Kangqi Ni; Lesa Tran Lu; Kristi Kincaid; John S. Hutchinson; Richard G. Baraniuk (AIED (1), 2024)

Leveraging Large Language Models for Next-Generation Educational Technologies. - Neil T. Heffernan; Rose E. Wang; Christopher MacLellan; Arto Hellas; Chenglu Li; Candace A. Walkington; Joshua Littenberg-Tobias; David Joyner; Steven Moore; Adish Singla; Zach A. Pardos; Maciej Pankiewicz; et al. (EDM, 2024)

Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning. - Shashank Sonkar; Naiming Liu; Richard G. Baraniuk (EMNLP (Findings), 2024)

MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education. - Shashank Sonkar; Naiming Liu; Myco Le; Richard G. Baraniuk (EMNLP (Findings), 2024)

Pedagogical Alignment of Large Language Models. - Shashank Sonkar; Kangqi Ni; Sapana Chaudhary; Richard G. Baraniuk (EMNLP (Findings), 2024)

Code Soliloquies for Accurate Calculations in Large Language Models. - Shashank Sonkar; Xinghe Chen; Myco Le; Naiming Liu; Debshila Basu Mallick; Richard G. Baraniuk (LAK, 2024)

Regressive Side Effects of Training Language Models to Mimic Student Misconceptions. - Shashank Sonkar; Naiming Liu; Richard G. Baraniuk (CoRR, 2024)

Many-Shot Regurgitation (MSR) Prompting. - Shashank Sonkar; Richard G. Baraniuk (CoRR, 2024)

MalAlgoQA: A Pedagogical Approach for Evaluating Counterfactual Reasoning Abilities. - Naiming Liu; Shashank Sonkar; Myco Le; Richard G. Baraniuk (CoRR, 2024)

LLM-based Cognitive Models of Students with Misconceptions. - Shashank Sonkar; Xinghe Chen; Naiming Liu; Richard G. Baraniuk; Mrinmaya Sachan (CoRR, 2024)

Atomic Learning Objectives Labeling: A High-Resolution Approach for Physics Education. - Naiming Liu; Shashank Sonkar; Debshila Basu Mallick; Richard G. Baraniuk; Zhongzhou Chen (CoRR, 2024)

Do LLMs Make Mistakes Like Students? Exploring Natural Alignments Between Language Models and Human Error Patterns. - Naiming Liu; Shashank Sonkar; Richard G. Baraniuk (AIED (4), 2025)

Many-Shot Regurgitation Prompting. - Shashank Sonkar; Naiming Liu; Richard G. Baraniuk (AIED (5), 2025)

Turing-Like Test for Personalized Educational AI. - Shashank Sonkar; Naiming Liu; Xinghe Chen; Richard G. Baraniuk (AIED (6), 2025)

Atomic Learning Objectives and LLMs Labeling: A High-Resolution Approach for Physics Education. - Naiming Liu; Shashank Sonkar; Debshila Basu Mallick; Richard G. Baraniuk; Zhongzhou Chen (LAK, 2025)

The Imitation Game for Educational AI. - Shashank Sonkar; Naiming Liu; Xinghe Chen; Richard G. Baraniuk (CoRR, 2025)

Do LLMs Make Mistakes Like Students? Exploring Natural Alignment between Language Models and Human Error Patterns. - Naiming Liu; Shashank Sonkar; Richard G. Baraniuk (CoRR, 2025)

CLEAR-3K: Assessing Causal Explanatory Capabilities in Language Models. - Naiming Liu; Richard G. Baraniuk; Shashank Sonkar (CoRR, 2025)