Customer-obsessed science

The increasing use of Retrieval-Augmented Generation (RAG) systems in various applications necessitates stringent protocols to ensure RAG systems’ accuracy, safety, and alignment with user intentions. In this paper, we introduce VERA (Validation and Evaluation of Retrieval-Augmented Systems), a framework designed to enhance the transparency and reliability of outputs from large language models (LLMs) that

Forecasting extrapolates the values of a time series into the future, and is crucial to optimize core operations for many businesses and organizations. Building machine learning (ML)-based forecasting applications presents a challenge though, due to non-stationary data and large numbers of time series. As there is no single dominating approach to forecasting, forecasting systems have to support a wide variety

We present Diffusion Soup, a compartmentalization method for Text-to-Image Generation that averages the weights of diffusion models trained on sharded data. By construction, our approach enables training-free continual learning and unlearning with no additional memory or inference costs, since models corresponding to data shards can be added or removed by re-averaging. We show that Diffusion Soup samples

Explicitly adding language information to multilingual ASR models during training has been shown to improve their performance. However, this also requires using language information during inference. In cascaded systems, this language label may come from external language identification models, which are susceptible to errors. In this work, we characterize the sensitivity to errors in language inputs of

Quantum computers have the potential to outperform classical computers in important tasks such as optimization and number factoring. They are characterized by limited connectivity, which necessitates the routing of their computational bits, known as qubits, to specific locations during program execution to carry out quantum operations. Traditionally, the NP-hard optimization problem of minimizing the routing