activity
20182025
most citedPhi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

163 citations · 234 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2025

The Bias is in the Details: An Assessment of Cognitive Bias in LLMs

R. Alexander Knipper, Charles S. Knipper, Kaiqi Zhang +3

As Large Language Models (LLMs) are increasingly embedded in real-world decision-making processes, it becomes crucial to examine the extent to which they exhibit cognitive biases.…

cs.CL2025★ 7 cited

Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs

Microsoft, :, Abdelrahman Abouelenin +73

We introduce Phi-4-Mini and Phi-4-Multimodal, compact yet highly capable language and multimodal models. Phi-4-Mini is a 3.8-billion-parameter language model trained on high-qualit…

cs.CL2024★ 2 cited

Phi-3 Safety Post-Training: Aligning Language Models with a "Break-Fix" Cycle

Emman Haider, Daniel Perez-Becker, Thomas Portet +28

Recent innovations in language model training have demonstrated that it is possible to create highly performant models that are small enough to run on a smartphone. As these models…

cs.CL2024★ 163 cited

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Marah Abdin, Jyoti Aneja, Hany Awadalla +126

We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal test…

cs.LG2021★ 1 cited

Disease Progression Modeling Workbench 360

Parthasarathy Suryanarayanan, Prithwish Chakraborty, Piyush Madan +9

In this work we introduce Disease Progression Modeling workbench 360 (DPM360) opensource clinical informatics framework for collaborative research and delivery of healthcare AI. DP…

cs.LG2021★ 1 cited

Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge

Prithwish Chakraborty, James Codella, Piyush Madan +22

Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains. However, these architectures have been limited in their ability…

cs.CY2020★ 37 cited

WNTRAC: AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19

Parthasarathy Suryanarayanan, Ching-Huei Tsou, Ananya Poddar +23

The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human society throughout the world. Against an emerging, highly transmissible disease…

cs.LG2020

A Canonical Architecture For Predictive Analytics on Longitudinal Patient Records

Parthasarathy Suryanarayanan, Bhavani Iyer, Prithwish Chakraborty +11

Many institutions within the healthcare ecosystem are making significant investments in AI technologies to optimize their business operations at lower cost with improved patient ou…

cs.LG2018★ 23 cited

Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration

Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei +6

Autonomous cyber-physical agents and systems play an increasingly large role in our lives. To ensure that agents behave in ways aligned with the values of the societies in which th…

cs.LG2018

Effect of secular trend in drug effectiveness study in real world data

Sharon Hensley Alford, Piyush Madan, Shilpa Mahatma +3

We discovered secular trend bias in a drug effectiveness study for a recently approved drug. We compared treatment outcomes between patients who received the newly approved drug an…