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TagsRA3: Mid-Training with Temporal Action Abstractions for Faster Reinforcement Learning (RL) Post-Training in Code...

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

AI

Sentient AI Releases ROMA: An Open-Source and AGI Focused Meta-Agent Framework for Building AI Agents with Hierarchical Task Execution

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AI

Meet OpenTSLM: A Family of Time-Series Language Models (TSLMs) Revolutionizing Medical Time-Series Analysis

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AI

A Coding Guide to Master Self-Supervised Learning with Lightly AI for Efficient Data Curation and Active Learning

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AI

Liquid AI Releases LFM2-8B-A1B: An On-Device Mixture-of-Experts with 8.3B Params and a 1.5B Active Params per Token

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AI

Meta Superintelligence Labs’ MetaEmbed Rethinks Multimodal Embeddings and Enables Test-Time Scaling with Flexible Late Interaction

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AI

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

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AI

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

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AI

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

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AI

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

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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...

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