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◬ AI & Machine Learning May 20, 2026
38 Cybersecurity M&A Deals in March 2026 Alone [Analysis] - tech-insider.org

38 Cybersecurity M&A Deals in March 2026 Alone [Analysis] tech-insider.org

tech-insider.org Read →
◬ AI & Machine Learning May 19, 2026
Google just redesigned the search box for the first time in 25 years — here’s why it matters more than you think.

For a quarter century, the Google search box has been one of the most recognizable interfaces in computing: a thin white rectangle, a blinking cursor, a few typed words, and a list of blue links. On T…

VentureBeat AI Read →
◬ AI & Machine Learning May 19, 2026
OlmoEarth v1.1: A more efficient family of models
Hugging Face Read →
◬ AI & Machine Learning May 19, 2026
Everything new in our Google AI subscriptions, fresh from I/O 2026

Introducing a $100 AI Ultra plan — plus, new features and benefits for Google AI Plus, Pro and Ultra subscribers.

Google AI Read →
◬ AI & Machine Learning May 19, 2026
A new era for AI Search

We shared the next step in our journey to bring together the best of a search engine with the best of AI.

Google AI Read →
◬ AI & Machine Learning May 19, 2026
Gemini 3.5: frontier intelligence with action

At Google I/O we released Gemini 3.5, our latest series of models combining frontier intelligence with action.

Google AI Read →
◬ AI & Machine Learning May 19, 2026
I/O 2026: Welcome to the agentic Gemini era

The latest from Google I/O: See how we’re helping you get more done with Gemini.

Google AI Read →
◬ AI & Machine Learning May 19, 2026
New ways to create and get things done in Google Workspace

Announcing new voice capabilities in Gmail, Docs and Keep, a new design tool called Google Pics and updates to AI Inbox.

Google AI Read →
◬ AI & Machine Learning May 19, 2026
How AI Mode is changing the way people search in the U.S.

One year after launch, see how AI Mode’s users are shifting from keywords to natural language queries.

Google AI Read →
◬ AI & Machine Learning May 19, 2026
I/O 2026

At Google I/O 2026, we shared how we’re making AI more helpful for everyone. See everything we announced.

Google AI Read →
◬ AI & Machine Learning May 19, 2026
Introducing the Ettin Reranker Family
Hugging Face Read →
◬ AI & Machine Learning May 19, 2026
How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study

arXiv:2605.16953v1 Announce Type: new Abstract: While AI-generated hallucinations pose considerable risks, the underlying cognitive mechanisms by which humans can successfully recognize or be misled b…

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction

arXiv:2605.16927v1 Announce Type: new Abstract: Clinical decision-making is a feedback system where risk estimates influence treatment, which in turn changes disease trajectories, and both shape clini…

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents

arXiv:2605.16909v1 Announce Type: new Abstract: Tool-using agents are increasingly expected to operate across realistic professional workflows, where they must interpret multimodal inputs, coordinate …

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
NGM: A Plug-and-Play Training-Free Memory Module for LLMs

arXiv:2605.16893v1 Announce Type: new Abstract: Recent studies introduce conditional memory modules that decouple knowledge storage from neural computation, enabling more direct knowledge access. Comp…

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities

arXiv:2605.16880v1 Announce Type: new Abstract: Multimodal magnetic resonance imaging (MRI) is crucial for brain tumor segmentation, with many methods leveraging its four key modalities to capture com…

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
Reasoning Can Be Restored by Correcting a Few Decision Tokens

arXiv:2605.16874v1 Announce Type: new Abstract: Large reasoning models (LRMs) substantially outperform their base LLM counterparts on challenging reasoning benchmarks, yet it remains poorly understood…

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
Learning to Learn from Multimodal Experience

arXiv:2605.16857v1 Announce Type: new Abstract: Experience-driven learning has emerged as a promising paradigm for enabling agents to improve from interaction trajectories by accumulating and reusing …

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
Artificial Adaptive Intelligence: The Missing Stage Between Narrow and General Intelligence

arXiv:2605.16844v1 Announce Type: new Abstract: Between the narrow systems we deploy and the general intelligence we speculate about lies an entire regime of machine behavior that has never received i…

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
Sketch Then Paint: Hierarchical Reinforcement Learning for Diffusion Multi-Modal Large Language Models

arXiv:2605.16842v1 Announce Type: new Abstract: Diffusion Multi-Modal Large Language Models (dMLLMs) are powerful for image generation, but optimizing them through reinforcement learning (RL) remains …

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
Voices in the Loop: Mapping Participatory AI

arXiv:2605.16827v1 Announce Type: new Abstract: Participatory approaches to artificial intelligence are increasingly documented across public, civic, and humanitarian settings, but evidence about how …

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
Multi-Paradigm Agent Interaction in Practice:A Systematic Analysis of Generator-Evaluator, ReAct Loop,and Adversarial Evaluation in the buddyMe Framework

arXiv:2605.16821v1 Announce Type: new Abstract: The rapid evolution of Large Language Model (LLM) agents has produced diverse interaction paradigms, yet few production systems integrate multiple parad…

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning

arXiv:2605.16757v1 Announce Type: new Abstract: Multi-agent language systems are often built as hand-designed workflows, where agents are assigned semantic roles and communication protocols are specif…

arXiv AI Read →
◬ AI & Machine Learning May 19, 2026
State Contamination in Memory-Augmented LLM Agents

arXiv:2605.16746v1 Announce Type: new Abstract: LLM agents increasingly rely on persistent state, including transcripts, summaries, retrieved context, and memory buffers, to support long-horizon inter…

arXiv AI Read →
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