Publications

You can also find my articles on my Google Scholar profile.

GNOME: Generating Negotiations through Open-Domain Mapping of Exchanges

Published in arXiv, 2024

Introduces GNOME, an automated framework that uses Large Language Models to generate synthetic open-domain negotiation dialogues from closed-domain datasets, addressing the limited generalizability of existing negotiation models. Experiments show that models trained on GNOME-generated data outperform state-of-the-art models in both domain-specific strategy prediction and generalization to novel domains, while reducing manual data curation efforts.

Recommended citation: Deshpande, D., Sinha, S., Kumar, A., Pal, D. & May, J. (2024). GNOME: Generating Negotiations through Open-Domain Mapping of Exchanges. ArXiv, abs/2406.10764. https://arxiv.org/abs/2305.12280

Contextualizing Argument Quality Assessment with Relevant Knowledge

Published in NAACL-2024, 2024

This work proposes SPARK: a novel method for scoring argument quality based on contextualization via relevant knowledge, and devise four augmentations that leverage large language models to provide feedback, infer hidden assumptions, supply a similar-quality argument, or a counterargument.

Recommended citation: Darshan Deshpande, Zhivar Sourati, Filip Ilievski, and Fred Morstatter. 2024. Contextualizing Argument Quality Assessment with Relevant Knowledge. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers), pages 316–326, Mexico City, Mexico. Association for Computational Linguistics. https://aclanthology.org/2024.naacl-short.28/

Robust Text Classification: Analyzing Prototype-Based Networks

Published in arXiv, 2023

A modular and comprehensive framework for studying Prototype Based Networks (PBNs), which includes different backbone architectures, backbone sizes, and objective functions is designed, which shows that the robustness of PBNs transfers to NLP classification tasks facing realistic perturbations.

Recommended citation: Sourati, Z., Deshpande, D., Ilievski, F., Gashteovski, K., & Saralajew, S. (2023). Robust Text Classification: Analyzing Prototype-Based Networks. ArXiv, abs/2311.06647. https://arxiv.org/abs/2311.06647

Robust and explainable identification of logical fallacies in natural language arguments

Published in Knowledge Based Systems, 2023

This paper formalizes prior theoretical work on logical fallacies into a comprehensive three-stage evaluation framework of detection, coarse- grained, and fine-grained classification, and employs three families of robust and explainable methods based on prototype reasoning, instance-based reasoning, and knowledge injection.

Recommended citation: Sourati, Z., Venkatesh, V. P. P., Deshpande, D., Rawlani, H., Ilievski, F., Sandlin, H., & Mermoud, A. (2023). Robust and explainable identification of logical fallacies in natural language arguments. Knowledge-Based Systems, 266, 110418. https://doi.org/10.1016/j.knosys.2023.110418 https://www.sciencedirect.com/science/article/pii/S0950705123001685