Large language models in medicine

AJ Thirunavukarasu, DSJ Ting, K Elangovan… - Nature medicine, 2023 - nature.com
Large language models (LLMs) can respond to free-text queries without being specifically
trained in the task in question, causing excitement and concern about their use in healthcare …

The future landscape of large language models in medicine

J Clusmann, FR Kolbinger, HS Muti, ZI Carrero… - Communications …, 2023 - nature.com
Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to
process and generate text. LLMs attracted substantial public attention after OpenAI's …

Alpacafarm: A simulation framework for methods that learn from human feedback

Y Dubois, CX Li, R Taori, T Zhang… - Advances in …, 2023 - proceedings.neurips.cc
Large language models (LLMs) such as ChatGPT have seen widespread adoption due to
their ability to follow user instructions well. Develo** these LLMs involves a complex yet …

Visionllm: Large language model is also an open-ended decoder for vision-centric tasks

W Wang, Z Chen, X Chen, J Wu… - Advances in …, 2024 - proceedings.neurips.cc
Large language models (LLMs) have notably accelerated progress towards artificial general
intelligence (AGI), with their impressive zero-shot capacity for user-tailored tasks, endowing …

How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites

Z Chen, W Wang, H Tian, S Ye, Z Gao, E Cui… - Science China …, 2024 - Springer
In this paper, we introduce InternVL 1.5, an open-source multimodal large language model
(MLLM) to bridge the capability gap between open-source and proprietary commercial …

Inference-time intervention: Eliciting truthful answers from a language model

K Li, O Patel, F Viégas, H Pfister… - Advances in Neural …, 2024 - proceedings.neurips.cc
Abstract We introduce Inference-Time Intervention (ITI), a technique designed to enhance
the" truthfulness" of large language models (LLMs). ITI operates by shifting model activations …

Challenges and applications of large language models

J Kaddour, J Harris, M Mozes, H Bradley… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Stablerep: Synthetic images from text-to-image models make strong visual representation learners

Y Tian, L Fan, P Isola, H Chang… - Advances in Neural …, 2023 - proceedings.neurips.cc
We investigate the potential of learning visual representations using synthetic images
generated by text-to-image models. This is a natural question in the light of the excellent …

Multimodal chain-of-thought reasoning in language models

Z Zhang, A Zhang, M Li, H Zhao, G Karypis… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) have shown impressive performance on complex reasoning
by leveraging chain-of-thought (CoT) prompting to generate intermediate reasoning chains …

Zephyr: Direct distillation of lm alignment

L Tunstall, E Beeching, N Lambert, N Rajani… - arxiv preprint arxiv …, 2023 - arxiv.org
We aim to produce a smaller language model that is aligned to user intent. Previous
research has shown that applying distilled supervised fine-tuning (dSFT) on larger models …