Papers by Sushant Kumar Ray
Are Large Language Models Economically Viable for Industry Deployment? (2026.acl-industry)
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Abdullah Mohammad, Sushant Kumar Ray, Pushkar Arora, Rafiq Ali, Ebad Shabbir, Gautam Siddharth Kashyap, Jiechao Gao, Usman Naseem
| Challenge: | Generative AI is increasingly deployed in healthcare, financial analytics, and conversational automation. |
| Approach: | They propose a framework that evaluates large language models across their full lifecycle on legacy GPUs. |
| Outcome: | The proposed framework evaluates LLMs across their full lifecycle on legacy GPUs. |
Do Large Language Models Reflect Demographic Pluralism in Safety? (2026.findings-eacl)
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Usman Naseem, Gautam Siddharth Kashyap, Sushant Kumar Ray, Rafiq Ali, Ebad Shabbir, Abdullah Mohammad
| Challenge: | Existing datasets that focus on demographics and safety are narrow in their annotator pools. |
| Approach: | They propose to decouple value framing from responses by modeling pluralism directly at the prompt level. |
| Outcome: | Demo-SafetyBench decouples value framing from responses to model pluralism at the prompt level. |
Do Clinical Question Answering Systems Really Need Specialised Medical Fine Tuning? (2026.eacl-industry)
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Sushant Kumar Ray, Gautam Siddharth Kashyap, Sahil Tripathi, Nipun Joshi, Vijay Govindarajan, Rafiq Ali, Jiechao Gao, Usman Naseem
| Challenge: | Clinical Question-Answering (CQA) industry systems rely on Large Language Models (LLMs). |
| Approach: | They propose a framework that applies alignment at inference time rather than through SFT to help CQA users achieve consistent reasoning. |
| Outcome: | MEDASSESS-X improves Accuracy, Factual Consistency and Safety by up to 50%. |