Papers by Saransh Sharma

3 papers
Text Takes Over: A Study of Modality Bias in Multimodal Intent Detection (2025.emnlp-main)

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Challenge: a new study examines the effectiveness of large language models and non-LLMs in multimodal intent detection . large-scale multimodal data integrations include text, audio, and visual inputs .
Approach: They propose a framework to debias multimodal intent detection datasets by using human evaluation.
Outcome: The proposed framework debiases the datasets and shows that mistral-7B outperforms most competitive models by approximately 9% on MIntRec-1 and 4% on MIndRec2.0.
FiRST: Finetuning Router-Selective Transformers for Input-Adaptive Latency Reduction (2025.findings-emnlp)

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Challenge: Existing approaches to improve latency via skipping layers have limitations . fiRST is a model-agnostic framework that reduces inference latency while maintaining quality .
Approach: They propose a model-agnostic framework that skips transformer layers during decoding . it is fully compatible with KV caching, enabling faster decoding while maintaining quality .
Outcome: a new framework reduces inference latency by using layer-specific routers to skip transformer layers during decoding.
An Answer is just the Start: Related Insight Generation for Open-Ended Document-Grounded QA (2026.findings-acl)

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Challenge: Existing QA benchmarks do not explicitly support document-grounded related insight generation . Existing document-based QA efforts focus on answering fact-based questions .
Approach: They propose a task to generate additional insights from a document collection that improves, extends or rethinks an initial answer to an open-ended question.
Outcome: The proposed task improves, extends, or rethinks an answer to an open-ended question.

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