Machine learning models for predicting in-hospital mortality in intensive care units (ICUs) are increasingly deployed across hospital systems with heterogeneous patient populations and outcome rates. Despite growing awareness of dataset shift, the calibration consequences of hospital-level prevalence variation remain u...
Aman Chandra H, Stuti Shivhare, Suyash Sahu· 2026 International Conferenc...· 0 citations
Access to legal information in India remains disproportionately limited due to the complexity of statutory language, jurisdictional specificity, and the absence of AI tools designed for the Indian legal context. General-purpose large language models (LLMs), while capable of broad question answering, frequently hallucin...
Sameer Kulkarni, Aman Chandra H, Saadhvi S et al.· 2026 International Conferenc...· 0 citations
Multilingual large language models (LLMs) are widely assumed to behave consistently regardless of the language in which a prompt is expressed. We challenge this assumption through a controlled empirical study in which language itself is isolated as the sole independent variable. We present 30 semantically equivalent pr...
Aman Chandra H, Sameer Kulkarni, S. Nithin et al.· 2026 International Conferenc...· 0 citations
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