activity
20232026
most citedILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Temporal Evidence Allocation For Longitudinal Clinical Retrieval: A Position And Technical Report

Soumya Ranjan Sahoo, Divya Bharti, Sanand Sasidharan

Electronic health records are written to support care, not retrieval. Across years of oncology notes, the primary diagnosis is restated in report after report, while the events tha…

cs.IR2026

Negation is Not Semantic: Diagnosing Dense Retrieval Failure Modes for Trade-offs in Contradiction-Aware Biomedical QA

Soumya Ranjan Sahoo, Gagan N., Sanand Sasidharan +1

Large Language Models (LLMs) have demonstrated strong capabilities in biomedical question answering, yet their tendency to generate plausible but unverified claims poses serious ri…

cs.CL2024★ 1 cited

ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler

Paramita Mirza, Viju Sudhi, Soumya Ranjan Sahoo +1

State-of-the-art intent classification (IC) and slot filling (SF) methods often rely on data-intensive deep learning models, limiting their practicality for industry applications.…

cs.CL2023★ 1 cited

InCA: Rethinking In-Car Conversational System Assessment Leveraging Large Language Models

Ken E. Friedl, Abbas Goher Khan, Soumya Ranjan Sahoo +3

The assessment of advanced generative large language models (LLMs) poses a significant challenge, given their heightened complexity in recent developments. Furthermore, evaluating…

cs.CL2023

CarExpert: Leveraging Large Language Models for In-Car Conversational Question Answering

Md Rashad Al Hasan Rony, Christian Suess, Sinchana Ramakanth Bhat +6

Large language models (LLMs) have demonstrated remarkable performance by following natural language instructions without fine-tuning them on domain-specific tasks and data. However…