Search Results for author: Aliakbar Nafar

Found 4 papers, 2 papers with code

Probabilistic Reasoning in Generative Large Language Models

no code implementations14 Feb 2024 Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi

This paper considers the challenges that Large Language Models (LLMs) face when reasoning over text that includes information involving uncertainty explicitly quantified via probability values.

Decision Making Mathematical Reasoning +1

Teaching Probabilistic Logical Reasoning to Transformers

no code implementations22 May 2023 Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi

In this paper, we evaluate the capability of transformer-based language models in making inferences over uncertain text that includes uncertain rules of reasoning.

Logical Reasoning Question Answering

GLUECons: A Generic Benchmark for Learning Under Constraints

1 code implementation16 Feb 2023 Hossein Rajaby Faghihi, Aliakbar Nafar, Chen Zheng, Roshanak Mirzaee, Yue Zhang, Andrzej Uszok, Alexander Wan, Tanawan Premsri, Dan Roth, Parisa Kordjamshidi

Recent research has shown that integrating domain knowledge into deep learning architectures is effective -- it helps reduce the amount of required data, improves the accuracy of the models' decisions, and improves the interpretability of models.

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