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Salesforce AI Introduces FOFPred: A Language-Driven Future Optical Flow Prediction Framework that Enables Improved Robot Control and Video Generation

Salesforce AI research team present FOFPred, a language driven future optical flow prediction framework that connects large vision language models with diffusion transformers for dense motion forecasting in control and video generation settings. FOFPred takes one or more images and a natural language instruction such as ‘moving the bottle from right to left’ and predicts…

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Black Forest Labs Releases FLUX.2 [klein]: Compact Flow Models for Interactive Visual Intelligence

Black Forest Labs releases FLUX.2 [klein], a compact image model family that targets interactive visual intelligence on consumer hardware. FLUX.2 [klein] extends the FLUX.2 line with sub second generation and editing, a unified architecture for text to image and image to image, and deployment options that range from local GPUs to cloud APIs, while keeping…

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New video generation model updates

Today, Veo is getting more expressive, with improvements that help you create more fun, creative, high-quality videos based on ingredient images, built directly for the mobile format. We’re excited to bring new creative possibilities for everyone from casual storytellers to professional filmmakers. We’re releasing: Improvements to Veo 3.1 Ingredients to Video, our capability that lets…

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Evaluating OCR-to-Markdown Systems Is Fundamentally Broken (and Why That’s Hard to Fix)

Evaluating OCR systems that convert PDFs or document images into Markdown is far more complex than it appears. Unlike plain text OCR, OCR-to-Markdown requires models to recover content, layout, reading order, and representation choices simultaneously. Today’s benchmarks attempt to score this with a mix of string matching, heuristic alignment, and format-specific rules—but in practice, these…

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5 Useful Python Scripts for Effective Feature Engineering

Image by Author   #  Introduction   As a machine learning practitioner, you know that feature engineering is painstaking, manual work. You need to create interaction terms between features, encode categorical variables properly, extract temporal patterns from dates, generate aggregations, and transform distributions. For each potential feature, you test whether it improves model performance, iterate…

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FACTS Benchmark Suite: a new way to systematically evaluate LLMs factuality

Large language models (LLMs) are increasingly becoming a primary source for information delivery across diverse use cases, so it’s important that their responses are factually accurate. In order to continue improving their performance on this industry-wide challenge, we have to better understand the types of use cases where models struggle to provide an accurate response…

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