Medical LLM
Medical LLMs are large language models adapted for healthcare applications, primarily aiming to improve medical information access, analysis, and decision-making. Current research focuses on enhancing reasoning capabilities through techniques like chain-of-thought prompting and dynamic reasoning trajectory search, as well as addressing biases and ensuring safety through careful preference alignment and guardrail implementation. These advancements hold significant promise for improving healthcare efficiency and patient care, but ongoing work is crucial to address challenges like bias mitigation, hallucination reduction, and robust evaluation in real-world clinical settings.
Papers
Generating Energy-efficient code with LLMs
Tom Cappendijk, Pepijn de Reus, Ana Oprescu
Legal Evalutions and Challenges of Large Language Models
Jiaqi Wang, Huan Zhao, Zhenyuan Yang, Peng Shu, Junhao Chen, Haobo Sun, Ruixi Liang, Shixin Li, Pengcheng Shi, Longjun Ma, Zongjia Liu, Zhengliang Liu, Tianyang Zhong, Yutong Zhang, Chong Ma, Xin Zhang, Tuo Zhang, Tianli Ding, Yudan Ren, Tianming Liu, Xi Jiang, Shu Zhang
Refusal in LLMs is an Affine Function
Thomas Marshall, Adam Scherlis, Nora Belrose
CoCoP: Enhancing Text Classification with LLM through Code Completion Prompt
Mohammad Mahdi Mohajeri, Mohammad Javad Dousti, Majid Nili Ahmadabadi
LLMStinger: Jailbreaking LLMs using RL fine-tuned LLMs
Piyush Jha, Arnav Arora, Vijay Ganesh
Evaluating World Models with LLM for Decision Making
Chang Yang, Xinrun Wang, Junzhe Jiang, Qinggang Zhang, Xiao Huang
Scholarly Wikidata: Population and Exploration of Conference Data in Wikidata using LLMs
Nandana Mihindukulasooriya, Sanju Tiwari, Daniil Dobriy, Finn Årup Nielsen, Tek Raj Chhetri, Axel Polleres
Towards Secure Intelligent O-RAN Architecture: Vulnerabilities, Threats and Promising Technical Solutions using LLMs
Mojdeh Karbalaee Motalleb, Chafika Benzaid, Tarik Taleb, Marcos Katz, Vahid Shah-Mansouri, JaeSeung Song
Leveraging LLMs for Predictive Insights in Food Policy and Behavioral Interventions
Micha Kaiser, Paul Lohmann, Peter Ochieng, Billy Shi, Cass R. Sunstein, Lucia A. Reisch
Tree-of-Table: Unleashing the Power of LLMs for Enhanced Large-Scale Table Understanding
Deyi Ji, Lanyun Zhu, Siqi Gao, Peng Xu, Hongtao Lu, Jieping Ye, Feng Zhao
Universal Response and Emergence of Induction in LLMs
Niclas Luick
Sniff AI: Is My 'Spicy' Your 'Spicy'? Exploring LLM's Perceptual Alignment with Human Smell Experiences
Shu Zhong, Zetao Zhou, Christopher Dawes, Giada Brianz, Marianna Obrist
1-800-SHARED-TASKS @ NLU of Devanagari Script Languages: Detection of Language, Hate Speech, and Targets using LLMs
Jebish Purbey, Siddartha Pullakhandam, Kanwal Mehreen, Muhammad Arham, Drishti Sharma, Ashay Srivastava, Ram Mohan Rao Kadiyala
Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs
Megh Thakkar, Yash More, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
Script-Strategy Aligned Generation: Aligning LLMs with Expert-Crafted Dialogue Scripts and Therapeutic Strategies for Psychotherapy
Xin Sun, Jan de Wit, Zhuying Li, Jiahuan Pei, Abdallah El Ali, Jos A.Bosch