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Latest updates for Meta-Learning

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venturebeat.com /1 month ago

MeMo's memory model lets teams upgrade their LLM without retraining it — and performance jumps 26%

Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context win...

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pandaily.com /1 week ago

Ant Group and HKUST(GZ) Propose Skill-MAS, Turning Multi-Agent Orchestration into Evolvable Meta-Skills

Ant Group and HKUST(GZ) introduce Skill-MAS, a framework that evolves multi-agent system design experience into reusable meta-skills, validated on DeepSeek-V4-Flash and other model...

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salesforce.com /1 month ago

Can Language Models Remember What They Learn?

Post-training methods (RLVR, On-policy distillation) are Episode-local Language models are getting better at learning from feedback during post-training. In reinforcement learning...

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marktechpost.com /3 days ago

Guide to Loop Engineering: How ‘autoresearch’ and ‘Bilevel Autoresearch’ Turn AI Agents Into Autonomous Machine Learning...

Most people still use AI like a 2015 search box. You type, you read, you type again. A newer pattern replaces that manual back-and-forth with a loop. This guide explains loop engin...

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medium.com /1 month ago

Beyond Self Refinement: Mitigating “Plausible Unsupported Success” via Cross Model Adversarial…

As Large Language Model (LLM) agents scale from executing basic tool use scripts to running complex, autonomous machine learning pipelines…Continue reading on Medium »

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marktechpost.com /1 month ago

Trajectory Releases a Concurrent Multi-LoRA Training Stack for Continual Learning, Reporting a 2.81Г— Experiment-Through...

Trajectory, working with UC Berkeley Sky Lab and Anyscale, built a concurrent multi-LoRA training stack for continual learning. It maps each RL experiment to a dedicated LoRA adapt...

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medium.com /1 month ago

AI Is Learning Human Behavior Faster Than Humans Learn AI

How the machines became expert students of human preference, taste, deception, and desire while most humans still cannot explain what a…Continue reading on Data Science Collective...

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inc.com /1 month ago

How AI Could Make Workplace Training More Human

The real skill now? Learning how to learn with AI.

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marktechpost.com /1 month ago

MEMO: A Modular Framework for Training a Dedicated Memory Model on New Knowledge Without Modifying LLM Parameters

Researchers from NUS, MIT, and A*STAR propose MEMO, a modular framework that encodes corpus knowledge into a separate trainable MEMORY model. The post MEMO: A Modular Framework for...

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pandaily.com /1 month ago

Xiaohongshu's Evolving-RL: A New Paradigm for Self-Evolving AI Agent Skills

Researchers from Xiaohongshu (RED), the influential Chinese lifestyle and social commerce platform, have published Evolving-RL, a novel reinforcement learning framework that enable...

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towardsdatascience.com /2 weeks ago

From Local LLM to Tool-Using Agent

Using Gemma 4, Ollama, OpenAI Agents SDK, and Tavily MCP to build a lightweight research agent The post From Local LLM to Tool-Using Agent appeared first on Towards Data Science.

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venturebeat.com /3 weeks ago

Researchers introduce Self-Harness, a framework that lets AI agents rewrite their own rules, boosting performance up to...

Not every company can or should build their own frontier AI language model. However, the harness controlling the model is something that most enterprises can and should customize f...

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venturebeat.com /3 weeks ago

Why agentic enterprises need to become learning systems

Presented by SplunkEvery day, organizations learn things their AI systems never get to use.A security analyst corrects an AI-generated investigation. A network engineer identifies...

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towardsdatascience.com /2 weeks ago

Water Cooler Small Talk, Ep. 11: Overfitting in RAG evaluation

Why memorizing for the exam doesn't mean you understand the subject The post Water Cooler Small Talk, Ep. 11: Overfitting in RAG evaluation appeared first on Towards Data Science.

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marktechpost.com /1 month ago

Hexo Labs Open-Sources SIA: A Self-Improving Agent That Updates Both the Harness and the Model Weights

Hexo Labs released SIA, an open-source self-improving loop, under an MIT license. A Feedback-Agent reads each run's trajectory, then either rewrites the scaffold or triggers a LoRA...

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marktechpost.com /6 days ago

Meta Superintelligence Labs Releases Muse Spark 1.1: A Multimodal Reasoning Model for Agentic Tasks on Meta Model API

Meta Superintelligence Labs released Muse Spark 1.1 on July 9, 2026, alongside a public preview of the Meta Model API. It is a multimodal reasoning model built for agentic tasks, w...

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ombulabs.ai /19 hours ago

Why LLM Benchmarks Don’t Predict Great Agents

Originally appeared on OmbuLabs Blog.Every time a new model launches, the conversation follows a familiar pattern. People pull up benchmark leaderboards. They compare scores acros...

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dzone.com /2 weeks ago

A Low-Latency Routing Pattern for Multiple Small Language Models

A multi-SLM platform creates value only when specialization does not introduce a new latency tier. Small language models are inexpensive enough to dedicate to focused work such as ...

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medium.com /1 month ago

Machine Learning: How Computers Learn from Data

Machine Learning: How Computers Learn from DataContinue reading on Medium »

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marktechpost.com /2 days ago

Stanford Researchers Introduce TRACE: A Capability-Targeted Agentic Training System That Turns Recurrent Agent Failures...

Agentic LLMs keep failing the same way because they lack specific, reusable capabilities. Stanford's TRACE diagnoses those gaps from an agent's own trajectories, synthesizes one ve...

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chvkrsubhash.medium.com /1 week ago

Optimizing LLM Training: Techniques for Faster, More Efficient, and Scalable Models

IntroductionContinue reading on Medium »

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medium.com /1 week ago

The Loop That Improves the Loop: Why Self Improving Agents Plateau (and How to Fix It)

A quiet assumption hiding inside every “self-improving” systemContinue reading on Medium »

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medium.com /3 weeks ago

AI Models Know When They’re Being Tested

The leaderboard you trust is just a performance, and the model is the one performingContinue reading on Medium »

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javacodegeeks.com /3 weeks ago

Anthropic Agent Skills Support in Spring AI

Large Language Models (LLMs) are rapidly evolving from simple text generators into intelligent agents capable of performing complex tasks. One of the latest advancements introduced...

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