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Offline Video-LLMs Can Now Understand Real-Time Streams: Apple Researchers Introduce StreamBridge...

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OpenAI presents a new blueprint for AI regulation that is its...

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Mercedes-Benz Virtual Assistant uses Google Conversational AI agent

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Sa2VA: A Unified AI Framework for Dense Grounded Video and Image...

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Natural Language Processing

What are Small Language Models (SLMs)?

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This AI Paper Introduces Toto: Autoregressive Video Models for Unified Image...

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R3GAN: A Simplified and Stable Baseline for Generative Adversarial Networks GANs

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Researchers from Fudan University and Shanghai AI Lab Introduces DOLPHIN: A...

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Meta AI Introduces CLUE (Constitutional MLLM JUdgE): An AI Framework Designed...

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Salesforce AI Introduces TACO: A New Family of Multimodal Action Models...

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Meet Search-o1: An AI Framework that Integrates the Agentic Search Workflow...

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Education

RL^V: Unifying Reasoning and Verification in Language Models through Value-Free Reinforcement...

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Implementing an LLM Agent with Tool Access Using MCP-Use

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A Step-by-Step Guide to Deploy a Fully Integrated Firecrawl-Powered MCP Server...

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Education

Reinforcement Learning, Not Fine-Tuning: Nemotron-Tool-N1 Trains LLMs to Use Tools with...

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RL^V: Unifying Reasoning and Verification in Language Models through Value-Free Reinforcement...

LLMs have gained outstanding reasoning capabilities through reinforcement learning (RL) on correctness rewards. Modern RL algorithms for LLMs, including GRPO, VinePPO, and Leave-one-out PPO, have moved away from traditional PPO approaches by eliminating the learned value function network in favor of empirically estimated returns. This reduces computational demands and...