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Salesforce AI Research Propose Programmatic VLM Evaluation (PROVE): A New Benchmarking Paradigm for Evaluating VLM Responses to Open-Ended Queries

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Researchers from Salesforce AI Research have proposed Programmatic VLM Evaluation (PROVE), a new benchmarking paradigm that evaluates VLM responses to open-ended visual queries. If you like our work, you will love our newsletter. Don’t Forget to join our 55k+ ML SubReddit.

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Google AI Research Examines Random Circuit Sampling (RCS) for Evaluating Quantum Computer Performance in the Presence of Noise

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Upcoming Live Webinar- Oct 29, 2024] The Best Platform for Serving Fine-Tuned Models: Predibase Inference Engine (Promoted) The post Google AI Research Examines Random Circuit Sampling (RCS) for Evaluating Quantum Computer Performance in the Presence of Noise appeared first on MarkTechPost.

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Salesforce AI Research Introduces BLIP-3-Video: A Multimodal Language Model for Videos Designed to Efficiently Capture Temporal Information Over Multiple Frames

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In response, researchers from Salesforce AI Research introduced BLIP-3-Video, an advanced VLM specifically designed to address the inefficiencies in video processing. All credit for this research goes to the researchers of this project. Check out the Paper and Project. Don’t Forget to join our 55k+ ML SubReddit.

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Allen Institute for AI Released olmOCR: A High-Performance Open Source Toolkit Designed to Convert PDFs and Document Images into Clean and Structured Plain Text

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Modern AI systems rely on vast datasets of token trillions to improve their accuracy and efficiency. Researchers at the Allen Institute for AI introduced olmOCR , an open-source Python toolkit designed to efficiently convert PDFs into structured plain text while preserving logical reading order.

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Google AI Researchers Propose ‘MODEL SWARMS’: A Collaborative Search Algorithm to Flexibly Adapt Diverse LLM Experts to Wide-Ranging Purposes

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Researchers from Google Cloud AI, Google DeepMind, and the University of Washington have proposed a new approach called MODEL SWARMS , which utilizes swarm intelligence to adapt LLMs through collaborative search in the weight space. If you like our work, you will love our newsletter. Don’t Forget to join our 50k+ ML SubReddit.

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SGLang: An Open-Source Inference Engine Transforming LLM Deployment through CPU Scheduling, Cache-Aware Load Balancing, and Rapid Structured Output Generation

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SGLang is an open-source inference engine designed by the SGLang team to address these challenges. It optimizes CPU and GPU resources during inference, achieving significantly higher throughput than many competitive solutions. Also,feel free to follow us on Twitter and dont forget to join our 75k+ ML SubReddit.

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This AI Research from Cohere for AI Compares Merging vs Data Mixing as a Recipe for Building High-Performant Aligned LLMs

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As AI technologies become globally pervasive, addressing the safety concerns that arise when models trained predominantly in English are deployed across various languages and cultural contexts is essential. To overcome these limitations, researchers from Cohere AI have introduced an innovative approach based on model merging.