Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches ...

In the field of generative AI media, the industry is transitioning from purely probabilistic pixel synthesis toward models capable of structural reasoning. Luma Labs has just released Uni-1, a ...

For visual generation, discrete autoregressive models often struggle with poor tokenizer reconstruction, difficulties in sampling from large vocabularies, and slow token-by-token generation speeds. We ...

Information retrieval systems are designed to satisfy a user. To make a user happy with the quality of their recall. It’s important we understand that. Every system and its inputs and outputs are ...

Anthropic gave AI a dose of "evil" during training to help it resist bad behavior later on. The company said the method works like a vaccine to build resilience. Anthropic's research comes as AI ...

Lightricks, the Israeli AI startup best known for viral mobile apps like Facetune and Videoleap, is pushing deeper into professional production territory with a technical milestone that sets it apart ...

DeepSeek and OpenAI’s o1 models performed the best across the various benchmarks, but all models still struggle in a range of tasks, so there is much more work to be done. AI models are advancing at a ...

Vector Autoregression (VAR) is a statistical model used to capture the linear interdependencies among multiple time series data. It generalizes the univariate autoregressive model to multiple time ...

ABSTRACT: To improve the efficiency of air quality analysis and the accuracy of predictions, this paper proposes a composite method based on Vector Autoregressive (VAR) and Random Forest (RF) models.

Abstract: The vector autoregressive (VAR) model is extensively employed for modelling dynamic processes, yet its scalability is challenged by an overwhelming growth in parameters when dealing with ...

Autoregressive LLMs are complex neural networks that generate coherent and contextually relevant text through sequential prediction. These LLms excel at handling large datasets and are very strong at ...