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Praveenkumar Kanithi

Observed names: Kanithi, Praveen K, Kanithi, Praveenkumar
OpenAlex ID: A5114847529
Tokenization to Transfer: Do Genomic Foundation Models Learn Good Representations?
2024 · Kirill Vishniakov, Karthik Viswanathan, et al. · bioRxiv (Cold Spring Harbor Laboratory) · 14
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Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches
2024 · Christophe, Clément, Kanithi, Praveen K, et al. · arXiv (Cornell University) · 14
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Med42-v2: A Suite of Clinical LLMs
2024 · Christophe, Clément, Kanithi, Praveen K, et al. · arXiv (Cornell University) · 12
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MEDIC: Comprehensive Evaluation of Leading Indicators for LLM Safety and Utility in Clinical Applications
2024 · Kanithi, Praveenkumar, Christophe, Clément, et al. · arXiv (Cornell University) · 9
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BioToken and BioFM – Biologically-Informed Tokenization Enables Accurate and Efficient Genomic Foundation Models
2025 · Aleksandr Medvedev, Karthik Viswanathan, et al. · bioRxiv (Cold Spring Harbor Laboratory) · 3
Named Clinical Entity Recognition Benchmark
2024 · Abdul, Wadood M, Pimentel, Marco AF, et al. · arXiv (Cornell University) · 2
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Gene42: Long-Range Genomic Foundation Model With Dense Attention
2025 · Vishniakov, Kirill, Amor, Boulbaba Ben, et al. · arXiv (Cornell University) · 1
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Bridging Language Barriers in Healthcare: A Study on Arabic LLMs
2025 · Saadi, Nada, Raha, Tathagata, et al. · arXiv (Cornell University) · 1
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Building Trust in Clinical LLMs: Bias Analysis and Dataset Transparency
2025 · Svetlana Maslenkova, Clement Christophe, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 1
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Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMs
2024 · Christophe, Clément, Raha, Tathagata, et al. · arXiv (Cornell University) · 1
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Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMs.
2024 · Clement Christophe, Tathagata Raha, et al. · 1
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Can large language models extract travel history from clinical text? A multi-annotator benchmark study
2026 · Praveenkumar Kanithi, Alyssa Pradhan, et al. · medRxiv
Cross-Examination Framework: A Task-Agnostic Diagnostic for Information Fidelity in Text-to-Text Generation
2026 · Raha, Tathagata, Christophe, Clement, et al. · arXiv (Cornell University)
Cross-Examination Framework: A Task-Agnostic Diagnostic for Information Fidelity in Text-to-Text Generation
2026 · Raha, Tathagata, Christophe, Clement, et al. · arXiv (Cornell University)
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Overalignment in Frontier LLMs: An Empirical Study of Sycophantic Behaviour in Healthcare
2026 · Christophe, Clément, Abdul, Wadood Mohammed, et al. · arXiv (Cornell University)
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Do Instruction-Tuned Models Always Perform Better Than Base Models? Evidence from Math and Domain-Shifted Benchmarks
2026 · Munjal, Prateek, Christophe, Clement, et al. · arXiv (Cornell University)
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Cross-Examination Framework: A Task-Agnostic Diagnostic for Information Fidelity in Text-to-Text Generation
2026 · Tathagata Raha, Clement Christophe, et al. · Annual Meeting of the Association for Computational Linguistics (ACL)
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Building Trust in Clinical LLMs: Bias Analysis and Dataset Transparency
2025 · Maslenkova, Svetlana, Christophe, Clement, et al. · arXiv (Cornell University)
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Beyond Metrics: A Critical Analysis of the Variability in Large Language Model Evaluation Frameworks
2024 · Pimentel, Marco AF, Christophe, Clément, et al. · arXiv (Cornell University)
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Works count: 20
Citation count: 59
H-index: 4
I10-index: 3
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