Papers by Sai Sree Harsha
Doc-React: Multi-page Heterogeneous Document Question-answering (2025.acl-short)
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Junda Wu, Yu Xia, Tong Yu, Xiang Chen, Sai Sree Harsha, Akash V Maharaj, Ruiyi Zhang, Victor Bursztyn, Sungchul Kim, Ryan A. Rossi, Julian McAuley, Yunyao Li, Ritwik Sinha
| Challenge: | Existing methods for integrating information across multiple modalities are suboptimal for multi-page, multimodal documents. |
| Approach: | They propose an adaptive iterative framework that balances information gain and uncertainty reduction at each step. |
| Outcome: | The proposed framework captures relevant multimodal content and achieves strong performance on complex QA tasks. |
RETAIN: Interactive Tool for Regression Testing Guided LLM Migration (2024.emnlp-demo)
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| Challenge: | Large Language Models (LLMs) are increasingly integrated into diverse applications. |
| Approach: | They propose a tool specifically designed for regression testing during LLM migrations. |
| Outcome: | RETAIN (REgression Testing guided LLM migrAtIoN) provides a tool specifically designed for regression testing during LLM migrations. |
Federated Retrieval Augmented Generation for Multi-Product Question Answering (2025.coling-industry)
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| Challenge: | Existing multi-domain RAG-QA approaches query all domains indiscriminately or rely on rigid resource selection. |
| Approach: | They propose a multi-product knowledge-augmented QA framework with probabilistic federated search across domains and relevant knowledge. |
| Outcome: | The proposed framework improves multi-product knowledge-augmented QA performance on Adobe products. |