Knowledge catalogue
arXiv:2605.08022v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have been proposed as biologically plausible and energy-efficient alternatives to conventional Artificial Neural Networ
David Welch / Bloomberg: GM plans to lay off IT workers in an effort to trim costs and bring in staff with skills in other tech areas; sources: the cuts will affect 500 to 600 employees — General Moto
arXiv:2410.06347v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) in robotics faces significant hurdles regarding sample efficiency and generalization across varying goals. While O
🤔Going to be in Vancouver tomorrow? 🧐Curious about whether or not scaling AI is a bad bet? 😎Catch TPN founder @zacharykarabell's chat with @GaryMarcus at @WebSummit at 10:20am. 🎟️Get your tickets here
arXiv:2602.14868v2 Announce Type: replace-cross Abstract: Reinforcement learning has emerged as a powerful paradigm for unlocking reasoning capabilities in language models. However, relying on sparse
Gonna keep retweeting, because this flawed move never dies: AI hype has become a giant game of bait and switch. the bait: we are going to make an AI that can solve any problem a expert human could sol
Criminal hackers have used artificial intelligence to develop a working zero-day exploit, the first confirmed case of its kind, according to a report released today by Google LLC’s Google Threat Intel
For the first time, Google says it has spotted and stopped a zero-day exploit developed with AI. According to a report from Google Threat Intelligence Group (GTIG), 'prominent cyber crime threat actor
Dustin Volz / New York Times: Google's TIG reports the first known example of hackers using AI to discover and weaponize a zero-day; TIG's chief analyst says “this is the tip of the iceberg” — The com
Samantha Subin / CNBC: Google's TIG says it likely thwarted the use of an AI-generated zero-day in a “mass exploitation event” and tools like OpenClaw are being used to find exploits — Google's Threat
arXiv:2605.07399v1 Announce Type: new Abstract: Diffusion Vision-Language Models (dVLMs), built upon the non-causal foundations of Diffusion Large Language Models (dLLMs), have demonstrated remarkable
arXiv:2605.07366v1 Announce Type: new Abstract: Adaptive rank allocation for LoRA, allocating more parameters to important layers and fewer to unimportant ones, consistently improves efficiency under
arXiv:2605.06755v1 Announce Type: cross Abstract: Reinforcement learning is widely used to improve the reasoning ability of large language models, especially when answers can be automatically checked.
arXiv:2605.07689v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is a standard algorithm for reinforcement learning from verifiable rewards, but its group-mean-centered advant
arXiv:2509.23370v2 Announce Type: replace Abstract: The CLIP model has established itself as a cornerstone of large-scale retrieval systems. However, its performance often degrades under distributiona
arXiv:2605.07961v1 Announce Type: new Abstract: Federated fine-tuning (FFT) has emerged as a privacy-preserving paradigm for collaboratively adapting large language models (LLMs). Built upon federated
arXiv:2605.07999v1 Announce Type: cross Abstract: Multiphoton photoreduction enables high-fidelity fabrication of complex 3D microstructures, yet reliable process-structure-property (PSP) prediction r
arXiv:2605.06671v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong potential for many mathematical problems. However, their performance on graph algorithmic tasks is
arXiv:2512.02991v2 Announce Type: replace Abstract: Despite significant progress in 3D object detection, point clouds remain challenging due to sparse data, incomplete structures, and limited semantic
arXiv:2605.08074v1 Announce Type: new Abstract: Conformal prediction (CP) provides a distribution-free approach to uncertainty quantification with finite-sample guarantees. However, applying CP to gra
arXiv:2605.07357v1 Announce Type: new Abstract: Reasoning-acting frameworks enhance large language models (LLMs) by interleaving reasoning with actions for dynamic information acquisition. However, ex
arXiv:2605.07812v1 Announce Type: cross Abstract: Advanced persistent threat (APT) attacks remain difficult to detect due to their stealth, adaptability, and use of legitimate system components. Prove
arXiv:2605.07454v1 Announce Type: new Abstract: In-context learning enables large language models to adapt to new tasks, but their performance is highly sensitive to the selected examples. Finding eff
great article, mostly focused on coding agents but applies elsewhere impo. aligns w a lot of my prior thoughts: - agents need scaffolding, not just smarter models - failures should become durable impr
Great essay by Tobi. Building an AI-native company? Go read it now. I couldn't resist visualizing it with my artifact generator. Biggest takeaway for me: 'The risk isn't that AI does the work. It's th
Grok just completely changed the game for real-time financial research. We just got the preview to 'Grok Skills,' and they look 10x more powerful than Claude Skills. In seconds, you can create workflo
Grok just previewed “Skills” and it's so next level it's not even funny You tell it: “Create a skill that grabs latest AI news from @testingcatalog” @Grok builds the WHOLE thing, behavior, instruction
arXiv:2605.06978v1 Announce Type: cross Abstract: Skill-augmented agents increasingly rely on large reusable skill libraries, but retrieving relevant skills is not the same as presenting usable contex
arXiv:2605.07053v1 Announce Type: cross Abstract: Benchmarks like GSM8K are popular measures of mathematical reasoning, but leaderboard gains can overstate true capability due to memorization of fixed
Executive Summary Since our February 2026 report on AI-related threat activity, Google Threat Intelligence Group (GTIG) has continued to track a maturing transition from nascent AI-enabled operations
arXiv:2605.07701v1 Announce Type: new Abstract: Classifier-Free Guidance (CFG) is a widely used mechanism for controlling diffusion-based generative models, yet its guidance scale is typically treated
arXiv:2603.19966v2 Announce Type: replace Abstract: Wind disturbances remain a key barrier to reliable autonomous navigation for lightweight quadrotors, where the rapidly varying airflow can destabili
arXiv:2602.11758v2 Announce Type: replace Abstract: Humanoid robots show promise for complex whole-body tasks in unstructured environments. Although Human-Object Interaction (HOI) has advanced, most m
arXiv:2605.07209v1 Announce Type: cross Abstract: We introduce a proxy-analyzer framework for detecting hallucinations in large language models. Instead of looking inside the generating model, our sys
arXiv:2509.08089v2 Announce Type: replace Abstract: Federated Learning (FL) enables distributed model training but is vulnerable to backdoor attacks, where malicious clients embed attacker-controlled
arXiv:2605.07250v1 Announce Type: cross Abstract: Recent advancements in visual context compression enable MLLMs to process ultra-long contexts efficiently by rendering text into images. However, we i
arXiv:2605.07211v1 Announce Type: cross Abstract: Mobile devices face diverse resource constraints and non-IID data class distributions, requiring fast on-device inference for local in-distribution (I
arXiv:2605.07397v1 Announce Type: new Abstract: After a somewhat rocky start, geometry and topology have established a foothold in machine learning. Message passing, either on graphs or higher-order c
Haven’t tried this but it seems very neat… Yet all of the demos (except maybe one) are the model being fun and/or annoying by correcting or reminding in real time. There are obvious uses for this sort
arXiv:2605.07472v1 Announce Type: cross Abstract: Insider threat detection assumes that an adaptive insider leaves behavioral residue distinguishing them from legitimate users. We test this assumption
arXiv:2605.07766v1 Announce Type: new Abstract: Many vision applications require identity consistency beyond strict biometric recognition, especially under non-frontal views or when facial cues are mi
arXiv:2605.07973v1 Announce Type: new Abstract: Text-to-image diffusion models can generate visually stunning images, yet, controlling what appears and how it appears, remains surprisingly difficult,
Thinking Machines, the AI company founded by former OpenAI CTO Mira Murati, announced Monday that it's working on something called 'interaction models.' The idea behind interaction models, according t
Simon Willison shares a technique for using Large Language Models directly from the command line using a shebang (#!) syntax, allowing scripts to be executed with LLM processing without explicit comma
arXiv:2605.06696v1 Announce Type: new Abstract: Collections of interacting AI agents can form coalitions, creating emergent group-level organization that is critical for AI safety and alignment. Howev
A Reddit discussion comparing HiDream-O1-Image-Dev (the newer, 8B pixel-native distilled model) with ZImage Base, examining stylistic and performance differences between the two text-to-image generati
HiDream-Studio v.01 was open-sourced on May 8, 2026, releasing the HiDream-O1-Image model (8B parameters) with both undistilled and distilled variants. HiDream-O1-Image is a unified image generative f
arXiv:2605.07512v1 Announce Type: new Abstract: Class-incremental learning aims to continuously acquire new knowledge while preserving previously learned information, thereby mitigating catastrophic f
arXiv:2605.07156v1 Announce Type: new Abstract: Precise molecular subtyping of gliomas, including isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion, directly guides surgical and therapeuti
arXiv:2605.07707v1 Announce Type: new Abstract: HTN planning is a variation of classical planning where, instead of searching for a linear sequence of actions, an algorithm decomposes higher-level tas
arXiv:2605.07254v1 Announce Type: new Abstract: Multi-view mesh reconstruction remains a core challenge in computer graphics and vision, especially for recovering high-frequency geometry from sparse o
arXiv:2605.07214v1 Announce Type: new Abstract: Large Language Models have recently emerged as a promising paradigm for automated heuristic design for NP-hard combinatorial optimization problems. Desp
arXiv:2605.07266v1 Announce Type: cross Abstract: Wireless foundation models are rapidly emerging as a key enabler of AI-native communication systems, yet a fundamental question remains unanswered: ho
In early 2026, ChatGPT expanded its user base across broader demographics and industry sectors, moving beyond early adopters to mainstream adoption. The report likely documents growth metrics, new use
arXiv:2510.01685v2 Announce Type: replace-cross Abstract: While large language models (LLMs) appear to be increasingly capable of solving compositional tasks, it is an open question whether they do so
This guide from OpenAI outlines strategies and best practices for enterprises implementing and scaling artificial intelligence across their organizations. It likely covers topics such as infrastructur
arXiv:2605.05340v2 Announce Type: replace-cross Abstract: As Vision-Language Models (VLMs) are increasingly deployed as autonomous cognitive cores for embodied assistants, evaluating their privacy awa
arXiv:2605.07492v1 Announce Type: new Abstract: The past year has seen over 20 open-source document parsing models, yet thefield still benchmarks almost exclusively on OmniDocBench, a 1,355-pagemanual
arXiv:2603.15001v2 Announce Type: replace-cross Abstract: Recently, it has been shown that the Stochastic Gradient Bandit (SGB) algorithm converges to a globally optimal policy with a constant learnin
In this post, we dive deep into the architecture and techniques we used to improve Miro’s bug routing, achieving six times fewer team reassignments and five times shorter time-to-resolution powered by