Publications

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

Comparative Analysis of Multi-Agent Architectures for Entity Relationship Classification

Published in 18th International Conference on Agents and Artificial Intelligence (ICAART 2026), 2026

A comparative study of multi-agent LLM architectures for entity relationship classification, evaluating how different agent decompositions and coordination strategies affect extraction quality.

Recommended citation: Maryam Berijanian, Kuldeep Singh, Amin Sehati (2026). "Comparative Analysis of Multi-Agent Architectures for Entity Relationship Classification" 18th International Conference on Agents and Artificial Intelligence (ICAART 2026). https://arxiv.org/abs/2506.02426

FinQAPT: Empowering Financial Decisions with End-to-End LLM-driven Question Answering Pipeline

Published in 5th ACM International Conference on AI in Finance (ICAIF 2024), New York, NY, 2024

FinQAPT is an end-to-end pipeline that closes the gaps in real-world financial question answering, from identifying relevant documents to reasoning over structured and unstructured data using LLMs, achieving state-of-the-art results on FinQA. Recognized as Best Paper Runner-Up at ACM ICAIF 2024.

Recommended citation: Kuldeep Singh, Simerjot Kaur, Charese Smiley (2024). "FinQAPT: Empowering Financial Decisions with End-to-End LLM-driven Question Answering Pipeline" 5th ACM International Conference on AI in Finance (ICAIF 2024). Best Paper Runner-Up. https://arxiv.org/abs/2410.13959

Soft Measures for Extracting Causal Collective Intelligence

Published in NLP4Science Workshop, EMNLP 2024, Miami, FL, 2024

This paper introduces soft, LLM-based measures for extracting causal collective intelligence from group discussions and text, moving beyond rigid rule-based extraction toward more flexible, nuanced causal representations.

Recommended citation: Maryam Berijanian, Spencer Dork, Kuldeep Singh (2024). "Soft Measures for Extracting Causal Collective Intelligence" NLP4Science Workshop, EMNLP 2024. https://arxiv.org/abs/2409.18911

NLP Driven Political Analysis of Subreddits

Published in 3rd International Conference on Data Intelligence and Cognitive Informatics, 2022, Tirunelveli, India, 2022

This paper explores diverse applications, delving into model mechanics and decision-making processes. Analyzing extensive text data, we employ interpretable algorithms to extract insights. Specifically, our study focuses on extracting information from political subreddits using sentiment analysis and classification model features.

Recommended citation: Singh, K., Anne, S.V.N.S. (2023). "NLP Driven Political Analysis of Subreddits" Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore.. 1(2). https://link.springer.com/chapter/10.1007/978-981-19-6004-8_54

Uncovering the Corona Virus Map Using Deep Entities and Relationship Models

Published in Arxiv Preprint, 2020

This paper focuses on extracting COVID-19 entities and relationships from a corpus of articles using a novel model. Through multi-task learning on annotated data, we train entity recognition and relationship discovery models. Employing concept masking, we prevent neural networks from functioning as associative memory, promoting contextual inference. Our findings reveal significant subnetworks, emphasize key terms, and illuminate past treatment modalities for related ailments.

Recommended citation: K Singh, P Singla, K Sarode, A Chandrakar and C Nichkawde (2020). " Uncovering the Corona Virus Map Using Deep Entities and Relationship Models" preprint ArXiv:2009.03068. 1(1). https://arxiv.org/abs/2009.03068