Papers by Sonali Singh

2 papers
Reinforcement Learning for Adversarial Query Generation to Enhance Relevance in Cold-Start Product Search (2025.acl-industry)

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Challenge: Existing methods do not incorporate feedback from the query relevance model, limiting their ability to generate queries that enhance product retrieval.
Approach: They propose an adversarial reinforcement learning framework that exposes weaknesses in query classification models by creating synthetic queries that augment the classifier's training set.
Outcome: The proposed framework improves query generation performance on public datasets and on proprietary datasets.
DiAL : Diversity Aware Listwise Ranking for Query Auto-Complete (2024.emnlp-industry)

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Challenge: Query Auto-Complete (QAC) is an essential search feature that helps users articulate their query by suggesting relevant completions as they type.
Approach: They propose a new framework that explicitly optimizes for diversity alongside customer feedback signals to balance relevance and diversity.
Outcome: The proposed framework yields an improvement of 8.5% in MRR and 22.8% in NDCG compared to the pairwise ranking approach on an eCommerce dataset.

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