Papers by Lavanya Sita Tekumalla

2 papers
ASK: Aspects and Retrieval based Hybrid Clarification in Task Oriented Dialogue Systems (2025.acl-industry)

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Challenge: Ambiguous user queries pose a challenge in task-oriented dialogue systems . Large Language Models (LLMs) rely on the top-k retrieved documents for clarification . traditional approaches lack principled mechanisms to determine when to use broad domain knowledge vs specific retrieved document context for clarification.
Approach: They propose a hybrid approach that dynamically chooses between document-based or aspect-based clarification based on query ambiguity.
Outcome: The proposed approach shows significant improvements over baselines on product troubleshooting and product search datasets.
MIRAGE: Metadata-guided Image Retrieval and Answer Generation for E-commerce Troubleshooting (2026.eacl-industry)

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Challenge: Existing multimodal systems often associate text and images based on embedding similarity or simple co-location, but fail to ensure that the linked image accurately depicts the specific product or component mentioned in a troubleshooting instruction.
Approach: They propose a metadata-first paradigm that treats structured metadata as a modality for multimodal grounding.
Outcome: The proposed model uses a semantic schema to capture product attributes and visual aspects.

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