Knowledge catalogue
arXiv:2604.07894v1 Announce Type: new Abstract: Personalized large language models (PLLMs) have garnered significant attention for their ability to align outputs with individual's needs and preference
Ultraplan, a planning feature in Claude, consumes approximately the same number of tokens and counts against subscription rate limits similarly to standard plan mode. Users should be aware that using
arXiv:2601.21463v2 Announce Type: replace-cross Abstract: Existing speech editing detection (SED) datasets are predominantly constructed using manual splicing or limited editing operations, resulting
arXiv:2604.08522v1 Announce Type: new Abstract: Video temporal grounding (VTG) is typically tackled with dataset-specific models that transfer poorly across domains and query styles. Recent efforts to
arXiv:2604.07264v1 Announce Type: cross Abstract: Operating LEO mega-constellations requires translating high-level operator intents ('reroute financial traffic away from polar links under 80 ms') int
arXiv:2603.15118v2 Announce Type: replace Abstract: We introduce VAREX (VARied-schema EXtraction), a benchmark for evaluating multimodal foundation models on structured data extraction from government
arXiv:2604.06644v1 Announce Type: cross Abstract: As deep learning inference is increasingly deployed in shared and cloud-based settings, a growing concern is input repurposing, in which data submitte
arXiv:2604.06182v1 Announce Type: cross Abstract: Existing online benchmarks for mobile GUI agents remain largely app-centric and task-homogeneous, failing to reflect the diversity and instability of
arXiv:2604.08401v1 Announce Type: cross Abstract: In large language model (LLM) agents, reasoning trajectories are treated as reliable internal beliefs for guiding actions and updating memory. However
arXiv:2604.06896v1 Announce Type: new Abstract: Epithelial tissues dynamically reshape through local mechanical interactions among cells, a process well captured by vertex models. Yet their many tunab
arXiv:2509.08016v2 Announce Type: replace Abstract: Video Large Language Models (VideoLLMs) face a critical bottleneck: increasing the number of input frames to capture fine-grained temporal detail le
arXiv:2510.23642v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently enabled coding agents capable of generating, executing, and revising visualization code. However, e
arXiv:2604.07705v1 Announce Type: new Abstract: Aerial vision-and-language navigation (Aerial VLN) aims to enable unmanned aerial vehicles (UAVs) to interpret natural language instructions and autonom
arXiv:2604.06440v1 Announce Type: cross Abstract: Visual prompting (VP) has emerged as a popular method to repurpose pretrained vision models for adaptation to downstream tasks. Unlike conventional mo
arXiv:2604.08509v1 Announce Type: new Abstract: Digital human generation has been studied for decades and supports a wide range of real-world applications. However, most existing systems are passively
arXiv:2604.07634v1 Announce Type: new Abstract: Streaming vision-language models (VLMs) continuously generate responses given an instruction prompt and an online stream of input frames. This is a core
arXiv:2603.18474v2 Announce Type: replace Abstract: Precise behavioral control of large language models (LLMs) is critical for complex applications. However, existing methods often incur high training
We pit LlamaParse against frontier models (Opus 4.6, Gemini 3.1 Pro, GPT-5.4) in a live OCR arena. ICYMI: the full workshop is on Youtube! Frontier VLMs are getting quite good at visual understanding,
We worked with @RWSGroup to fine-tune our Command translation model, which improved language and cultural expertise. Now, that model is the “brain” that powers RWS’ Language Weaver AI translation solu
arXiv:2604.06277v1 Announce Type: new Abstract: Existing hallucination detection methods for large language models (LLMs) rely on external verification at inference time, requiring gold answers, retri
arXiv:2604.06464v1 Announce Type: new Abstract: Conformal prediction provides distribution-free prediction intervals with finite-sample coverage guarantees, and recent work by Snell & Griffiths refra
what he said 🗣️ the very best agents today obsessively tailor the harness layer around the model I’m looking at you “5 things I learned from the Claude code leak” bros 👀 orchestration patterns, tool d
arXiv:2604.06995v1 Announce Type: new Abstract: Existing Graphical User Interface (GUI) reasoning tasks remain challenging, particularly in UI understanding. Current methods typically rely on direct s
Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more. Tip: Not
arXiv:2510.12476v2 Announce Type: replace Abstract: Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this abi
arXiv:2604.06422v1 Announce Type: cross Abstract: Understanding when Vision-Language Models (VLMs) will behave unexpectedly, whether models can reliably predict their own behavior, and if models adher
arXiv:2604.08281v1 Announce Type: new Abstract: Large reasoning models (LRMs) have achieved strong performance enhancement through scaling test time computation, but due to the inherent limitations of
arXiv:2510.26241v5 Announce Type: replace-cross Abstract: Modern vision-language models (VLMs) excel at many multimodal tasks, yet their grasp of temporal information in video remains weak and has not
arXiv:2604.07834v1 Announce Type: new Abstract: This paper presents an LLM-driven approach for constructing diverse social media datasets to measure and compare loneliness in the caregiver and non-car
Wrapped up the 3-day AI Engineer conference in London. Key takeaways: Planning & verification > implementation. Humans define what to build and validate it works. AI handles the coding. The harness ma
Yet another illustration of why LLMs aren’t even close to being AGI. The world’s best LLMs are still terrible at poker. We put each model into a 200bb heads-up NLHE match against GTO Wizard AI. The be
arXiv:2503.06717v3 Announce Type: replace Abstract: Interactive segmentation uses real-time user inputs, such as mouse clicks, to iteratively refine model predictions. Although not originally designed
A bit over a decade ago, we got fuzzers. A fuzzer is an automated vulnerability-finder that repeatedly runs a target program with semi-random inputs. One particular fuzzer, American Fuzzy Lop, was not
Editor’s note: This blog post outlines Google Cloud’s GPU AI/ML infrastructure reliability strategy, and will be updated with links to new community articles as they appear. As we enter the era of mul
After playing with it a bit, Meta's Muse Spark Thinking is fine so far, but really doesn't match the current Big Three models. It also is a bit... weird. Like some strange language & tone, a little lo
Application security posture management company Apiiro Ltd. today announced the launch of a new command-line interface designed to bring application security directly into artificial intelligence-driv
Mobile app security solutions provider Appknox today announced the launch of KnoxIQ, an artificial intelligence-native vulnerability assessment capability that introduces a new prioritization and reme
Artificial intelligence computing company Blaize Holdings Inc. today announced the launch of Blaize AI Services, a new platform designed to help AI infrastructure providers and enterprises deploy prod
Claude Agent SDK tracing in LangSmith just got an upgrade. Now you can trace: → Subagents → Child runs inside MCP tools → Cost tracking + more Update to the latest Python SDK to try it out. Docs: http
Claude Cowork, now generally available! We released Claude Cowork as a research preview 12 weeks ago. Since then, millions of people have made it part of how they work - and hundreds of thousands more
Day 1 of @aiDotEngineer in London – what a ride! 🤖 Ash Prabaker & Andrew Wilson from Anthropic on 'How to Build Agents That Run for Hours (Without Losing the Plot)' – spoiler: stop letting your agents
Deep Agents or @LangChain? Just use the right tool for the right job great q! deepagents has more 'batteries included', which langchain v1 is a very minimalistic agent harness if you are doing more co
every engineer at anthropic has been using mythos for ~1.5 months. meanwhile, their uptime is horrendous, claude code still has rendering bugs, etc. one could conclude that it won't be the end of soft
extremely fun jamming with Harrison on all things analytics, agents and evals! I have like 20 more hours worth of takes and opinions in this space and going on the pod uncorked them, more to come for
Florida Attorney General James Uthmeier is launching an investigation into OpenAI over public safety and national security risks, as reported earlier by Reuters. In a statement on Thursday, Uthmeier s
France is transitioning government desktops to Linux, with each ministry required to formalize its implementation plan by autumn 2026. https://linuxiac.com/france-launches-government-linux-desktop-pla
Give me one minute, and I’ll improve your Claude Code experience immediately. This is the first skill I built. And it’s the skill I use most often. *drumroll* It’s a SCREENSHOT skill. And honestly, I’
Google's latest upgrade for Gemini will allow the chatbot to generate interactive 3D models and simulations in response to your questions. With the new feature, you may see options to rotate the AI-ge
great q! deepagents has more 'batteries included', which langchain v1 is a very minimalistic agent harness if you are doing more complex workflows (eg claude code for X) -> deepagents if you want some
Grok is the AI to use if you value truth Grok 4.20 Non-Hallucination rate improved to even higher than previous highest Just days ago, it hit a record-breaking 78% Non-Hallucination Rate - already #1
Grok Law Grok-4.20 just ranked #1 in Legal & Government on Chatbot Arena It’s officially outperforming Anthropic’s Opus 4.6 and Google’s Gemini 3.1 Pro Grok is actively helping people navigate real la
Having a model like Gemma 4, which is perfectly adequate for everyday use in many cases, runs locally, is free, and secure, still feels unreal. We have a very good AI that costs nothing, uses hardly a
Here is my free workshop on building multi-agent systems, I presented at the @aiDotEngineer London conference together with @Whats_AI. It has code, slides and soon a 2-hour video diving deep into how
I just gave a workshop at @aiDotEngineer in London on building real multi-agent systems. The best part was hearing people laugh, interrupt us with questions.. You could feel they were following, think
If you want an example of what this looks like in practice, check out the '/research-docs' skill I created for Claude Code https://x.com/jerryjliu0/status/2041564207750246904?s=20 I built a Claude Cod
if you want claude's managed agents w/o model provider lock in, this is the path! `deepagents deploy` lets you deploy an agent built on our model agnostic, open source harness in minutes you can easil
Introducing Gemma 4 31B from @GoogleDeepMind on Together AI. AI natives can now use Gemma 4 31B on Together and benefit from reliable inference for multimodal reasoning, tool use, and agentic workflow
Artificial intelligence is proving to be a big bet for many companies across the enterprise landscape, and the gamblers are getting nervous. A survey of 2,400 global employees and C-suite leaders rele
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere l
This paper was accepted at the Workshop on Memory for LLM-Based Agentic Systems at ICLR. Language models have consistently grown to compress more world knowledge into their parameters, but the knowled