A5084817430- Topic Modeling
- Artificial Intelligence in Healthcare and Education
- Misinformation and Its Impacts
- Machine Learning in Healthcare
- Colorectal and Anal Carcinomas
- Colorectal Cancer Surgical Treatments
- Intracerebral and Subarachnoid Hemorrhage Research
- Artificial Intelligence in Law
- Hate Speech and Cyberbullying Detection
- Cerebral Venous Sinus Thrombosis
- Cancer Diagnosis and Treatment
- Legal Language and Interpretation
- Radiomics and Machine Learning in Medical Imaging
- Gastric Cancer Management and Outcomes
- Neurosurgical Procedures and Complications
- Computational and Text Analysis Methods
- Political Influence and Corporate Strategies
École Polytechnique Fédérale de Lausanne
2024
Fondazione Bruno Kessler
2024
Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made harness and improve LLMs' knowledge reasoning capacities, the resulting are either closed-source (e.g., PaLM, GPT-4) or limited in scale (<= 13B parameters), which restricts their abilities. In this work, we large-scale LLMs by releasing MEDITRON: a suite of open-source with 7B 70B parameters adapted domain. MEDITRON builds on Llama-2 (through our adaptation Nvidia's...
<title>Abstract</title> Can large language models (LLMs) create tailor-made, convincing arguments to promote false or misleading narratives online? Early work has found that LLMs can generate content perceived on par with, even more persuasive than, human-written messages. However, there is still limited evidence regarding LLMs' capabilities in direct conversations with humans—the scenario these are usually deployed at. In this pre-registered study, we analyze the power of AI-driven...
The development and popularization of large language models (LLMs) have raised concerns that they will be used to create tailor-made, convincing arguments push false or misleading narratives online. Early work has found can generate content perceived as at least on par often more persuasive than human-written messages. However, there is still limited knowledge about LLMs' capabilities in direct conversations with human counterparts how personalization improve their performance. In this...
Abstract Large language and multimodal models (LLMs LMMs) will transform access to medical knowledge clinical decision support. However, the current leading systems fall short of this promise, as they are either limited in scale, which restricts their capabilities, closed-source, limits extensions scrutiny that can be applied them, or not sufficiently adapted settings, inhibits practical use. In work, we democratize large-scale AI by developing MEDITRON: a suite open-source LLMs LMMs with 7B...
We present a method based on natural language processing (NLP), for studying the influence of interest groups (lobbies) in law-making process European Parliament (EP). collect and analyze novel datasets lobbies' position papers speeches made by members EP (MEPs). By comparing these texts basis semantic similarity entailment, we are able to discover interpretable links between MEPs lobbies. In absence ground-truth dataset such links, perform an indirect validation discovered with dataset,...