Large language models in medicine
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 …
trained in the task in question, causing excitement and concern about their use in healthcare …
The future landscape of large language models in medicine
Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to
process and generate text. LLMs attracted substantial public attention after OpenAI's …
process and generate text. LLMs attracted substantial public attention after OpenAI's …
Alpacafarm: A simulation framework for methods that learn from human feedback
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 …
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
Large language models (LLMs) have notably accelerated progress towards artificial general
intelligence (AGI), with their impressive zero-shot capacity for user-tailored tasks, endowing …
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
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 …
(MLLM) to bridge the capability gap between open-source and proprietary commercial …
Inference-time intervention: Eliciting truthful answers from a language model
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 …
the" truthfulness" of large language models (LLMs). ITI operates by shifting model activations …
Challenges and applications of large language models
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 …
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
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 …
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
Large language models (LLMs) have shown impressive performance on complex reasoning
by leveraging chain-of-thought (CoT) prompting to generate intermediate reasoning chains …
by leveraging chain-of-thought (CoT) prompting to generate intermediate reasoning chains …
Zephyr: Direct distillation of lm alignment
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 …
research has shown that applying distilled supervised fine-tuning (dSFT) on larger models …