arXiv AI

CoPlan: A Trustworthy Co-Intelligence Interface for Care Planning through Role-Based Contestable Argument Graphs

arXiv:2608. 05107v1 Announce Type: new Abstract: AI-supported care planning can help clinicians, patients, caregivers, and care teams coordinate complex decisions across clinical, functional, psychosocial, and environmental needs.

arXiv AI

Aug 7

Adaptive Arena-based Contestable Argumentative Network-of-Experts for Open-Ended Care Plan Coordination

arXiv:2608. 05391v1 Announce Type: new Abstract: Care plan coordination demands synthesizing heterogeneous clinical, functional, and psychosocial information across multiple professional disciplines, where monolithic LLM pipelines cannot perform in a transparent or safe manner.

By Truong Thanh Hung Nguyen, Hoang-Loc Cao, Phuc Ho, Phuc Truong Loc Nguyen, Ren\'e Richard, Hung Cao

llms agents fine-tuning safety

arXiv AI

Jun 2

CAREAgent: Clinical Agent with Structured Reasoning and Tool-Integrated for Order Generation

arXiv:2606. 01094v1 Announce Type: new Abstract: Clinical order generation serves as a critical bridge between clinical decision-making and real-world practice, translating medical decisions into concrete and executable orders.

By Ruihui Hou, Ziyue Huai, Chennuo Zhang, Ziyan Liu, Siran Zhao, Yao Yu, Jie Zhai, Tong Ruan

agents reinforcement-learning fine-tuning benchmarks

arXiv AI

1d ago

ETHOS: Towards a Modular Ethics Framework for Clinical Multi-Agent Systems

arXiv:2608. 15424v1 Announce Type: cross Abstract: The rapid adoption of large language models has enabled the development of clinical multi-agent systems (MAS) capable of integrating multimodal patient data and supporting increasingly complex clinical decision-making.

By Rakesh Sharma, Sydney Pugh, Cameron Beeche, Pankhuri Singhal, Rachel Wu, Margaret Eby, Jeffrey Duda, James Gee, Kyra O'Brien, Hersh Sagreiya, Marina Serper, Victoria Gershuni, Angela Bradbury, Anurag Verma, Eric Eaton, Kevin B. Johnson, Walter Witschey

llms rag agents multimodal safety

arXiv AI

Aug 12

ComBodied Agents: a New Paradigm of Human-Centric Agentic AI

arXiv:2608. 10915v1 Announce Type: new Abstract: After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication.

By Qianggang Ding, Xingyao Wang, Rui Feng, Zhibin Wang, Feixiang Wang, Kelong Mao, Hao Sun, Zhiyao Luo, Jiankai Tang, Lei Li, Jiadong Guo, Minheng Ni, Weicong Lin, Chenxi Yang, Hongxiang Gao, Zhenghua Chen, Yang Bai, Min Wu, Jun Cheng, Huazhu Fu, Dacheng Tao, Bang Liu

agents robotics multimodal benchmarks safety

arXiv AI

Jul 20

Cura 1T: Specialized Model for Agentic Healthcare

arXiv:2607. 15314v1 Announce Type: new Abstract: Healthcare spans high-stakes communication, expert reasoning, and workflow execution, yet specialized LLMs that cover these use cases together remain limited.

By actAVA AI, :, Haolin Chen, Leon Qi, Steve Brown, Deon Metelski, Tao Xia, Joonyul Lee, Qixuan Wang, Kevin Riley, Frank Wang, Weiran Yao

llms agents benchmarks

arXiv AI

Jul 17

JEEVHITAA -- An HCAI Ecosystem to Support Collective Care

arXiv:2512. 06364v4 Announce Type: replace-cross Abstract: Current mobile health platforms are predominantly individual-centric and lack the support for coordinated, auditable multi-actor workflows.

By Shyama Sastha Krishnamoorthy Srinivasan, Harsh Pala, Mohan Kumar, Pushpendra Singh

llms rag safety

arXiv Machine Learning

Jun 4

VentAgent: When LLMs Learn to Breathe -- Multi-Objective Arbitration for ARDS Ventilation

arXiv:2606. 04632v1 Announce Type: new Abstract: Mechanical ventilation for Acute Respiratory Distress Syndrome (ARDS) requires balancing competing physiological goals, including oxygenation, lung protection, and acid-base homeostasis.

By Teqi Hao, Yuxuan Fu, Xiaoyu Tan, Shaojie Shi, Bohao Lv, Yinghui Xu, Xihe Qiu

llms agents reinforcement-learning benchmarks safety

arXiv AI

Jul 15

First, do NOHARM: a medical safety benchmark and randomized study of physician and AI teaming on clinical consultations

arXiv:2512. 01241v4 Announce Type: replace-cross Abstract: Large language models (LLMs) and medical AI tools are routinely used by physicians and patients for medical advice, yet their clinical safety profiles remain poorly characterized.

By David Wu, Fateme Nateghi Haredasht, Saloni Kumar Maharaj, Priyank Jain, Jessica Tran, Matthew Gwiazdon, Arjun Rustagi, Jenelle Jindal, Jacob M. Koshy, Vinay Kadiyala, Anup Agarwal, Bassman Tappuni, Brianna French, Sirus Jesudasen, Christopher V. Cosgriff, Rebanta Chakraborty, Jillian Caldwell, Susan Ziolkowski, David J. Iberri, Robert Diep, Rahul S. Dalal, Kira L. Newman, Kristin Galetta, J. Carl Pallais, Nancy Wei, Kathleen M. Buchheit, David I. Hong, Vartan Pahalyants, Ernest Y. Lee, Allen Shih, Tamara B. Kaplan, Vishnu Ravi, Sarita Khemani, Thomas A. Buckley, April S. Liang, Daniel Shirvani, Advait Patil, Nicholas Marshall, Kanav Chopra, Joel Koh, Adi Badhwar, Anastasia Perez, Austin J. Schoeffler, Mahbuba Tusty, Chase M. Walton, Liam G. McCoy, David J. H. Wu, Yingjie Weng, Sumant Ranji, Kevin Schulman, Nigam H. Shah, Jason Hom, Arnold Milstein, Arjun K. Manrai, Adam Rodman, Jonathan H. Chen, Ethan Goh

llms rag agents benchmarks safety

arXiv AI

Jun 16

Toward Vibe Medicine: A Self-Evolving Multi-Agent Framework for Clinical Decision Support

arXiv:2606. 15504v1 Announce Type: new Abstract: In recent years, the advances of large language models and autonomous agents have revolutionized the healthcare field, facilitating diagnosis and improving treatment results.

By Qianxue Zhang, Yiming Ren, Shihuan Qin, Xiao Zhang, Liao Zhang, Jinyang Huang, Zhengliang Liu, Chenbin Liu, Hongying Feng, Jingyuan Chen, Yuzhen Ding, Weihang You, Hanqi Jiang, Yi Pan, Yifan Zhou, Junhao Chen, Lifeng Chen, Wei Liu, Tianming Liu, Zengren Zhao, Lian Zhang

llms agents multimodal safety

arXiv AI

Jul 7

Toward Trustworthy Large Language Model Agents in Healthcare

arXiv:2607. 05055v1 Announce Type: new Abstract: Healthcare appointment scheduling remains a persistent operational bottleneck, driven by manual coordination, fragmented legacy systems, and high administrative overhead.

By Hadi Hasan, Safaa Salman, Adam Tai Abou Dargham, Ammar Mohanna, Ali Chehab

llms rag agents benchmarks safety

arXiv AI

Jun 19

MedRLM: Recursive Multimodal Health Intelligence for Long-Context Clinical Reasoning, Sensor-Guided Screening, Evidence-Grounded Decision Support, and Community-to-Tertiary Referral Optimization

arXiv:2606. 20164v1 Announce Type: cross Abstract: Real-world clinical decision support requires reasoning over heterogeneous and longitudinal patient information rather than answering isolated medical questions.

By Aueaphum Aueawatthanaphisut

llms rag agents nlp multimodal

arXiv AI

5d ago

MARC v1: An Open-Source Multi-Agent Framework for Clinical AI Reasoning and Coordination

arXiv:2608. 13476v1 Announce Type: new Abstract: We present Multi-Agent Reasoning and Coordination (MARC), an open-source framework that replaces monolithic LLM prompting with deterministic multi-agent orchestration for clinical reasoning.

By Saisha Shetty, Satvik Tripathi, Austin Lin, Colin Zhao, Theodore Kim, Don Enwerem, Jacinta Arnold, Shahriar Faghani, Tessa S Cook

llms agents

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