TagsMeta AI Open-Sources OpenZL: A Format-Aware Compression Framework with a Universal Decoder

Tag: Meta AI Open-Sources OpenZL: A Format-Aware Compression Framework with a Universal Decoder

AI

Sigmoidal Scaling Curves Make Reinforcement Learning RL Post-Training Predictable for LLMs

Mr Hossain - October 17, 2025 0

AI

Agentic Context Engineering (ACE): Self-Improving LLMs via Evolving Contexts, Not Fine-Tuning

Mr Hossain - October 10, 2025 0

AI

Google Open-Sources an MCP Server for the Google Ads API, Bringing LLM-Native Access to Ads Data

Mr Hossain - October 10, 2025 0

AI

What are ‘Computer-Use Agents’? From Web to OS—A Technical Explainer

Mr Hossain - October 10, 2025 0

AI

Microsoft Research Releases Skala: a Deep-Learning Exchange–Correlation Functional Targeting Hybrid-Level Accuracy at Semi-Local Cost

Mr Hossain - October 10, 2025 0

AI

Tiny Recursive Model (TRM): A Tiny 7M Model that Surpass DeepSeek-R1, Gemini 2.5 pro, and o3-mini at Reasoning on both ARG-AGI 1 and ARC-AGI...

Mr Hossain - October 9, 2025 0

AI

RA3: Mid-Training with Temporal Action Abstractions for Faster Reinforcement Learning (RL) Post-Training in Code LLMs

Mr Hossain - October 9, 2025 0

AI

Stanford Researchers Released AgentFlow: In-the-Flow Reinforcement Learning RL for Modular, Tool-Using AI Agents

Mr Hossain - October 8, 2025 0

AI

Anthropic AI Releases Petri: An Open-Source Framework for Automated Auditing by Using AI Agents to Test the Behaviors of Target Models on Diverse Scenarios

Mr Hossain - October 8, 2025 0

AI

Model Context Protocol (MCP) vs Function Calling vs OpenAPI Tools — When to Use Each?

Mr Hossain - October 8, 2025 0

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