Speculative RAG consists of two components: (1) a specialist RAG drafter, and (2) a generalist RAG verifier. First, the base model’s knowledge retriever retrieves related documents from the knowledge base. Then, Speculative RAG offloads computational burden to the specialist RAG drafter, a small LM specialized in answering questions using retrieved documents and not expected to […]

Users have more choices for listening to music than ever before. Popular services boast of massive and varied catalogs. The YouTube Music catalog, for example, has over 100M songs globally. It follows that item recommendations are a core part of these products. Recommender systems make sense of the item catalog and are critical for tuning

We use LLaVA-v1.5, a widely used open-sourced MLLM, as our base model and train it using our contrastive tuning framework (HALVA). We then evaluate its performance on object hallucination mitigation and general visual question answering tasks (VQA) against fine-tuning–based approaches, HA-DPO and EOS. We consider LLaVA-v1.5 as the lower bound and GPT-4V as a strong

Introduction Imagine yourself a decade ago, jumping directly into the present shock of conversing naturally with an encyclopedic AI that crafts images, writes code, and debates philosophy. Won’t this technology almost certainly transform society — and hasn’t AI’s impact on us so far been a mixed-bag? Thus it’s no surprise that so many conversations these

Responsibility & Safety Published 2 August 2024 Authors Nahema Marchal and Rachel Xu New research analyzes the misuse of multimodal generative AI today, in order to help build safer and more responsible technologies Generative artificial intelligence (AI) models that can produce image, text, audio, video and more are enabling a new era of creativity and

Models Published 31 July 2024 Authors Language Model Interpretability team Announcing a comprehensive, open suite of sparse autoencoders for language model interpretability. To create an artificial intelligence (AI) language model, researchers build a system that learns from vast amounts of data without human guidance. As a result, the inner workings of language models are often

Many existing tools allow us to edit the photographs we take, from making an object in a photo pop to visualizing what a spare room might look like in the color mauve. Smoothly controllable (or parametric) edits are ideal as they provide precise control over how shiny an object appears (e.g., a coffee cup) or

Acknowledgements We thank the International Mathematical Olympiad organization for their support. AlphaProof development was led by Thomas Hubert, Rishi Mehta and Laurent Sartran; AlphaGeometry 2 and natural language reasoning efforts were led by Thang Luong. AlphaProof was developed with key contributions from Hussain Masoom, Aja Huang, Miklós Z. Horváth, Tom Zahavy, Vivek Veeriah, Eric Wieser,

Unfortunately, there are few large datasets that pair PPG data with long-term cardiovascular outcomes. In order to get a statistically useful number of such outcomes in a general population, a dataset needs to be quite large, and typically should cover a span of 5–10 years. Recently, Biobanks have become a popular way to collect such

Although traditional climate models have been improving over the decades, they often generate errors and have biases due to scientists’ incomplete understanding of how Earth’s climate works and how the models are built. These models divide the globe into cubes — typically 50–100 km on each horizontal side — that extend from the surface up