Aliakbar Nafar

According to our database, Aliakbar Nafar authored at least 10 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization.

Aliakbar Nafar, Kristen Brent Venable, Zijun Cui, Parisa Kordjamshidi

CoRR, May, 2025

Learning vs Retrieval: The Role of In-Context Examples in Regression with Large Language Models.

Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Reasoning over Uncertain Text by Generative Large Language Models.

Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Learning vs Retrieval: The Role of In-Context Examples in Regression with LLMs.

Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi

CoRR, 2024

Probabilistic Reasoning in Generative Large Language Models.

Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi

CoRR, 2024

Prompt2DeModel: Declarative Neuro-Symbolic Modeling with Natural Language.

Hossein Rajaby Faghihi, Aliakbar Nafar, Andrzej Uszok, Hamid R. Karimian, Parisa Kordjamshidi

Proceedings of the Neural-Symbolic Learning and Reasoning - 18th International Conference, 2024

Teaching Probabilistic Logical Reasoning to Transformers.

Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

2023

GLUECons: A Generic Benchmark for Learning under Constraints.

Hossein Rajaby Faghihi, Aliakbar Nafar, Chen Zheng, Roshanak Mirzaee, Yue Zhang, Andrzej Uszok, Alexander Wan, Tanawan Premsri, Dan Roth, Parisa Kordjamshidi

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

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

DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in Deep Learning.

Hossein Rajaby Faghihi, Quan Guo, Andrzej Uszok, Aliakbar Nafar, Parisa Kordjamshidi

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2021