Symbolic Reinforcement Learning Framework with Incremental Learning of Rule-based Policy. - Kinjal Basu 002; Elmer Salazar; Huaduo Wang; Joaquín Arias; Parth Padalkar; Gopal Gupta 001 (ICLP Workshops, 2022)

NeSyFOLD: Extracting Logic Programs from Convolutional Neural Networks. - Parth Padalkar; Huaduo Wang; Gopal Gupta 001 (ICLP Workshops, 2023)

NeSyFOLD: A System for Generating Logic-based Explanations from Convolutional Neural Networks. - Parth Padalkar; Huaduo Wang; Gopal Gupta 001 (CoRR, 2023)

Reliable Natural Language Understanding with Large Language Models and Answer Set Programming. - Abhiramon Rajasekharan; Yankai Zeng; Parth Padalkar; Gopal Gupta 001 (ICLP, 2023)

MACOptions: Multi-Agent Learning with Centralized Controller and Options Framework. - Alakh Aggarwal; Rishita Bansal; Parth Padalkar; Sriraam Natarajan (CoRR, 2023)

Using Logic Programming and Kernel-Grouping for Improving Interpretability of Convolutional Neural Networks. - Parth Padalkar; Gopal Gupta 001 (CoRR, 2023)

Prolog: Past, Present, and Future. - Gopal Gupta 001; Elmer Salazar; Farhad Shakerin; Joaquín Arias; Sarat Chandra Varanasi; Kinjal Basu 002; Huaduo Wang; Fang Li 010; Serdar Erbatur; Parth Padalkar; Abhiramon Rajasekharan; Yankai Zeng; et al. (Prolog: The Next 50 Years, 2023)

Logic-Based Explainable and Incremental Machine Learning. - Gopal Gupta 001; Huaduo Wang; Kinjal Basu 002; Farhad Shakerin; Elmer Salazar; Sarat Chandra Varanasi; Parth Padalkar; Sopam Dasgupta (Prolog: The Next 50 Years, 2023)

NeSyFOLD: A Framework for Interpretable Image Classification. - Parth Padalkar; Huaduo Wang; Gopal Gupta 001 (AAAI, 2024)

Using Logic Programming and Kernel-Grouping for Improving Interpretability of Convolutional Neural Networks. - Parth Padalkar; Huaduo Wang; Gopal Gupta 001 (PADL, 2024)

Automated Interactive Domain-Specific Conversational Agents that Understand Human Dialogs. - Yankai Zeng; Abhiramon Rajasekharan; Parth Padalkar; Kinjal Basu 002; Joaquín Arias; Gopal Gupta 001 (PADL, 2024)

A Neurosymbolic Framework for Bias Correction in CNNs. - Parth Padalkar; Natalia Slusarz; Ekaterina Komendantskaya; Gopal Gupta 001 (CoRR, 2024)

A Neurosymbolic Framework for Bias Correction in Convolutional Neural Networks. - Parth Padalkar; Natalia Slusarz; Ekaterina Komendantskaya; Gopal Gupta 001 (Theory Pract. Log. Program., 2024)

Improving Interpretability and Accuracy in Neuro-Symbolic Rule Extraction Using Class-Specific Sparse Filters. - Parth Padalkar; Jaeseong Lee; Shiyi Wei; Gopal Gupta 001 (CoRR, 2025)

Symbolic Rule Extraction from Attention-Guided Sparse Representations in Vision Transformers. - Parth Padalkar; Gopal Gupta 001 (CoRR, 2025)