DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in Deep Learning. - Hossein Rajaby Faghihi; Quan Guo; Andrzej Uszok; Aliakbar Nafar; Parisa Kordjamshidi (EMNLP (Demos), 2021)

DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in Deep Learning. - Hossein Rajaby Faghihi; Quan Guo; Andrzej Uszok; Aliakbar Nafar; Elaheh Raisi; Parisa Kordjamshidi (CoRR, 2021)

GLUECons: A Generic Benchmark for Learning under Constraints. - Hossein Rajaby Faghihi; Aliakbar Nafar; Chen Zheng; Roshanak Mirzaee; Yue Zhang 004; Andrzej Uszok; Alexander Wan; Tanawan Premsri; Dan Roth; Parisa Kordjamshidi (AAAI, 2023)

Teaching Probabilistic Logical Reasoning to Transformers. - Aliakbar Nafar; Kristen Brent Venable; Parisa Kordjamshidi (EACL (Findings), 2024)

Prompt2DeModel: Declarative Neuro-Symbolic Modeling with Natural Language. - Hossein Rajaby Faghihi; Aliakbar Nafar; Andrzej Uszok; Hamid R. Karimian; Parisa Kordjamshidi (NeSy (2), 2024)

Probabilistic Reasoning in Generative Large Language Models. - Aliakbar Nafar; Kristen Brent Venable; Parisa Kordjamshidi (CoRR, 2024)

Learning vs Retrieval: The Role of In-Context Examples in Regression with LLMs. - Aliakbar Nafar; Kristen Brent Venable; Parisa Kordjamshidi (CoRR, 2024)

Reasoning over Uncertain Text by Generative Large Language Models. - Aliakbar Nafar; Kristen Brent Venable; Parisa Kordjamshidi (AAAI, 2025)

Learning vs Retrieval: The Role of In-Context Examples in Regression with Large Language Models. - Aliakbar Nafar; Kristen Brent Venable; Parisa Kordjamshidi (NAACL (Long Papers), 2025)

Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization. - Aliakbar Nafar; Kristen Brent Venable; Zijun Cui; Parisa Kordjamshidi (CoRR, 2025)