Papers by Apoorva Singh
Agent-Ops: A Multi-Agent Orchestration Framework for End-to-End SOP Automation in E-Commerce Operations (2026.acl-industry)
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| Challenge: | Existing Large Language Models fail to execute multistep operational workflows requiring precise procedural adherence. |
| Approach: | They propose an end-to-end multi-agent framework automating Standard Operating Procedures in e-commerce. |
| Outcome: | The proposed framework achieves 85-97% accuracy and a 94.2% execution consistency in e-commerce . it is based on a human-AI framework that transforms ambiguous documentation into automation-ready specifications . |
Federated Meta-Learning for Emotion and Sentiment Aware Multi-modal Complaint Identification (2023.emnlp-main)
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| Challenge: | Existing studies on complaint identification are limited to text. |
| Approach: | They propose a meta-learning-based multi-modal multi-task framework for identifying complaints using emotion recognition and sentiment analysis as auxiliary tasks. |
| Outcome: | The proposed framework outperforms baselines and state-of-the-art approaches in centralized and federated meta-learning settings. |
Peeking inside the black box: A Commonsense-aware Generative Framework for Explainable Complaint Detection (2023.acl-long)
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| Challenge: | Complaining is an expression of negative emotions communicated due to a discrepancy between reality and expectations. |
| Approach: | They propose to use an explainable complaint dataset to generate a commonsense-aware generative framework that can predict the complaint cause, severity level, emotion, and polarity of the text. |
| Outcome: | The proposed model can predict the complaint cause, severity level, emotion, and polarity of the text in addition to detecting whether it is a complaint or not. |