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NVIDIA AI Introduces PivotRL: A New AI Framework Achieving High Agentic Accuracy With 4x Fewer Rollout Turns Efficiently
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NVIDIA AI Introduces PivotRL: A New AI Framework Achieving High Agentic Accuracy With 4x Fewer Rollout Turns Efficiently

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Post-training Large Language Models (LLMs) for long-horizon agentic tasks—such as software engineering, web browsing, and complex tool use—presents a persistent […]

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Google Introduces TurboQuant: A New Compression Algorithm that Reduces LLM Key-Value Cache Memory by 6x and Delivers Up to 8x Speedup, All with Zero Accuracy Loss

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The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. […]

Paged Attention in Large Language Models LLMs
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Paged Attention in Large Language Models LLMs

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When running LLMs at scale, the real limitation is GPU memory rather than compute, mainly because each request requires a […]

A Coding Implementation to Design Self-Evolving Skill Engine with OpenSpace for Skill Learning, Token Efficiency, and Collective Intelligence
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A Coding Implementation to Design Self-Evolving Skill Engine with OpenSpace for Skill Learning, Token Efficiency, and Collective Intelligence

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In this tutorial, we explore OpenSpace, a self-evolving skill engine developed by HKUDS that makes AI agents smarter, more cost-efficient, […]

This AI Paper Introduces TinyLoRA, A 13-Parameter Fine-Tuning Method That Reaches 91.8 Percent GSM8K on Qwen2.5-7B
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This AI Paper Introduces TinyLoRA, A 13-Parameter Fine-Tuning Method That Reaches 91.8 Percent GSM8K on Qwen2.5-7B

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Researchers from FAIR at Meta, Cornell University, and Carnegie Mellon University have demonstrated that large language models (LLMs) can learn […]

Yann LeCun’s New LeWorldModel (LeWM) Research Targets JEPA Collapse in Pixel-Based Predictive World Modeling
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Yann LeCun’s New LeWorldModel (LeWM) Research Targets JEPA Collapse in Pixel-Based Predictive World Modeling

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World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, […]

Meta AI’s New Hyperagents Don’t Just Solve Tasks—They Rewrite the Rules of How They Learn
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Meta AI’s New Hyperagents Don’t Just Solve Tasks—They Rewrite the Rules of How They Learn

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The dream of recursive self-improvement in AI—where a system doesn’t just get better at a task, but gets better at […]

Luma Labs Launches Uni-1: The Autoregressive Transformer Model that Reasons through Intentions Before Generating Images
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Luma Labs Launches Uni-1: The Autoregressive Transformer Model that Reasons through Intentions Before Generating Images

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In the field of generative AI media, the industry is transitioning from purely probabilistic pixel synthesis toward models capable of […]

How BM25 and RAG Retrieve Information Differently?
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How BM25 and RAG Retrieve Information Differently?

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When you type a query into a search engine, something has to decide which documents are actually relevant — and […]

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent
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Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

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In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building […]

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