41 citations · 60 across the 15 of their papers we have counts for
16 papers
Accelerating Scientific Research with Gemini in the Real-World
Samuel Schmidgall, Xiaokai Zhu, Marian Shaw +32
We present an extension and comprehensive real-world validation of Co-Scientist, a Gemini-based multi-agent system designed to accelerate end-to-end scientific research across hypo…
Towards Expert-level Medical AI for Real-time Video Consultations
Mahvish Nagda, Jihyeon Lee, Matthew Thompson +37
Audio-visual interaction is the standard for patient-physician consultations, enabling natural communication and effective assessment of illness through non-verbal cues. While text…
ResidencyRL: Reinforcement Learning in Simulated Clinical Environments
Valentin Liévin, Samuel Schmidgall, Tim Strother +32
In medical education, physicians convert academic knowledge into clinical expertise through residency: years of training across thousands of encounters, with diverse sources of fee…
MatrAIx: Simulating the World with 8.3 Billion Persona Agents
Xiaomin Li, Yuexing Hao, Jianheng Hou +90
Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…
Gemma 4 Technical Report
Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320
We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…
Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure
Moritz Schlager, Friederike Jungmann, Samuel Schmidgall +12
Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and expensive user studies. However, existin…
SymptomAI: Toward a Conversational AI Agent for Everyday Symptom Assessment
Joseph Breda, Fadi Yousif, Beszel Hawkins +30
Language models excel at diagnostic assessments on curated medical case-studies and vignettes, performing on par with, or better than, clinical professionals. However, existing stu…
TeamBench: Evaluating Agent Coordination under Enforced Role Separation
Yubin Kim, Chanwoo Park, Taehan Kim +9
Agent systems often decompose a task across multiple roles, but these roles are typically specified by prompts rather than enforced by access controls. Without enforcement, a team…
MedGemma 1.5 Technical Report
Andrew Sellergren, Chufan Gao, Fereshteh Mahvar +39
We introduce MedGemma 1.5 4B, the latest model in the MedGemma collection. MedGemma 1.5 expands on MedGemma 1 by integrating additional capabilities: high-dimensional medical imagi…
An AI Co-Data-Scientist for Prioritizing Candidate Biomarkers from Wearable Sensor Data
Yubin Kim, Salman Rahman, Samuel Schmidgall +33
Wearable devices generate continuous physiological and behavioral data, but converting these signals into clinically reviewable biomarker hypotheses remains labor-intensive. We int…
Proof of Time: A Benchmark for Evaluating Scientific Idea Judgments
Bingyang Ye, Shan Chen, Jingxuan Tu +4
Large language models are increasingly being used to assess and forecast research ideas, yet we lack scalable ways to evaluate the quality of models' judgments about these scientif…
Towards a Science of Scaling Agent Systems
Yubin Kim, Ken Gu, Chanwoo Park +17
Agents, language model-based systems capable of reasoning, planning, and acting are widely adopted in real-world tasks, yet how their performance changes as these systems scale acr…
MedGemma Technical Report
Andrew Sellergren, Sahar Kazemzadeh, Tiam Jaroensri +78
Artificial intelligence (AI) has significant potential in healthcare applications, but its training and deployment faces challenges due to healthcare's diverse data, complex tasks,…
AgentRxiv: Towards Collaborative Autonomous Research
Samuel Schmidgall, Michael Moor
Progress in scientific discovery is rarely the result of a single "Eureka" moment, but is rather the product of hundreds of scientists incrementally working together toward a commo…
SurGen: Text-Guided Diffusion Model for Surgical Video Generation
Joseph Cho, Samuel Schmidgall, Cyril Zakka +4
Diffusion-based video generation models have made significant strides, producing outputs with improved visual fidelity, temporal coherence, and user control. These advancements hol…
GP-VLS: A general-purpose vision language model for surgery
Samuel Schmidgall, Joseph Cho, Cyril Zakka +1
Surgery requires comprehensive medical knowledge, visual assessment skills, and procedural expertise. While recent surgical AI models have focused on solving task-specific problems…