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NVIDIA advances AI frontiers with CES 2025 announcements

AI News

Much like the impact of large language models on generative AI, Cosmos represents a new frontier for AI applications in robotics and autonomous systems. Pras Velagapudi, CTO at Agility, comments: Data scarcity and variability are key challenges to successful learning in robot environments.

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CMU Researchers Release Pangea-7B: A Fully Open Multimodal Large Language Models MLLMs for 39 Languages

Marktechpost

Despite recent advances in multimodal large language models (MLLMs), the development of these models has largely centered around English and Western-centric datasets. Moreover, PANGEA matches or even outperforms proprietary models like Gemini-1.5-Pro If you like our work, you will love our newsletter.

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VulScribeR: A Large Language Model-Based Approach for Generating Diverse and Realistic Vulnerable Code Samples

Marktechpost

VulScribeR employs large language models (LLMs) to generate diverse and realistic vulnerable code samples through three strategies: Mutation, Injection, and Extension. The success of VulScribeR highlights the importance of large-scale data augmentation in the field of vulnerability detection.

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Google DeepMind Researchers Introduce Diffusion Augmented Agents: A Machine Learning Framework for Efficient Exploration and Transfer Learning

Marktechpost

A major issue in RL is the data scarcity in embodied AI, where agents must interact with physical environments. This problem is exacerbated by the need for substantial reward-labeled data to train agents effectively. The large language model is the central controller, guiding the vision language and diffusion models.

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Open Artificial Knowledge (OAK) Dataset: A Large-Scale Resource for AI Research Derived from Wikipedia’s Main Categories

Marktechpost

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has highlighted the critical need for large, diverse, and high-quality datasets to train and evaluate foundation models. OAK dataset offers a comprehensive resource for AI research, derived from Wikipedia’s main categories.

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LEAN-GitHub: A Large-Scale Dataset for Advancing Automated Theorem Proving

Marktechpost

Large language models (LLMs) show promise in solving high-school-level math problems using proof assistants, yet their performance still needs to improve due to data scarcity. Formal languages require significant expertise, resulting in limited corpora. If you like our work, you will love our newsletter.

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Meta AI Researchers Introduce Token-Level Detective Reward Model (TLDR) to Provide Fine-Grained Annotations for Large Vision Language Models

Marktechpost

The model’s performance is evaluated using three distinct accuracy metrics: token-level accuracy for individual token assessment, sentence-level accuracy for evaluating coherent text segments, and response-level accuracy for overall output evaluation. If you like our work, you will love our newsletter.