Publications de Mahammad Ismayilzada

Evaluating Morphological Compositional Generalization in Large Language Models

Large language models (LLMs) have demonstrated significant progress in various natural language generation and understanding tasks. However, their linguistic generalization capabilities remain questionable, raising doubts about whether these models learn l ...

Association for Computational Linguistics2025

Exploring Defeasibility in Causal Reasoning

Boi Faltings, Antoine Bosselut, Debjit Paul, Mahammad Ismayilzada, Lazar Milikic

Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of strengthening argume ...

2024

kogito: A Commonsense Knowledge Inference Toolkit

Antoine Bosselut, Mahammad Ismayilzada

In this paper, we present kogito, an open-source tool for generating commonsense inferences about situations described in text. kogito provides an intuitive and extensible interface to interact with natural language generation models that can be used for h ...

Assoc Computational Linguistics-Acl2023

REFINER: Reasoning Feedback on Intermediate Representations

Boi Faltings, Robert West, Maxime Jean Julien Peyrard, Antoine Bosselut, Beatriz Maria Borges Ribeiro, Debjit Paul, Mahammad Ismayilzada

Language models (LMs) have recently shown remarkable performance on reasoning tasks by explicitly generating intermediate inferences, e.g., chain-of-thought prompting. However, these intermediate inference steps may be in- appropriate deductions from the i ...

2023

CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks

Antoine Bosselut, Debjit Paul, Mahammad Ismayilzada, Syrielle Mathilde Marie Montariol

Recent efforts in natural language processing (NLP) commonsense reasoning research have yielded a considerable number of new datasets and benchmarks. However, most of these datasets formulate commonsense reasoning challenges in artificial scenarios that ar ...

Association for Computational Linguistics2023