Knowledge catalogue
arXiv:2610.19051v1 Announce Type: cross Abstract: Coordinators that act on what they infer about teammates are usually certified by the accuracy of those inferences. We argue that accuracy is the wron
Today we’re releasing Muse Spark Open, the most capable US open-weight model to date. Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step r
arXiv:2610.16352v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a critical phase in the post-training pipeline of large language models (LLMs). As the frontier of LLM capabi
arXiv:2610.17751v1 Announce Type: cross Abstract: Large language model (LLM)-based multi-agent systems (MAS) are commonly organized around two coordination regimes. Centralized coordination provides e
Insightful paper on recursive self-improvement with a frozen LLM. (bookmark it) Memento 3 clears every level of all 25 public ARC-AGI-3 games and uses 44% of the human action count. The underlying LLM
arXiv:2610.18807v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) enables large language models (LLMs) to learn from multi-turn interactions with verifiable outcomes. Textual skills
arXiv:2610.17726v1 Announce Type: new Abstract: Large language model (LLM) agents excel at complex, multi-step tasks but suffer from catastrophic forgetting during continual learning--acquiring new sk
arXiv:2610.15929v1 Announce Type: new Abstract: Recent trackers built on foundation models such as the Segment Anything Model (SAM) achieve strong performance by propagating object masks through memor
Sovereign AI control is becoming a business continuity issue as autonomous agents take on essential enterprise workflows. Keeping data within national boundaries addresses part of the challenge, but o
Exa just passed $100m in annualized revenue. We've grown almost exactly 10x per year for 3 years. We now handle 2 billion requests a month from 200k+ teams. And it’s still so early: We predict agents
Enterprise management software company Workday Inc. today announced that it wants to turn its existing knowledge of people, money and business rules into an operational foundation for agentic artifici
arXiv:2610.12666v1 Announce Type: cross Abstract: We introduce iRAG, a human-in-the-loop decision-support system combining Retrieval-Augmented Generation (RAG) with Hybrid Decision-Making. Unlike conv
separating artifacts from the agent makes sense for sharing and cross-AI collaboration No vendor lock-in for your artifacts. Sites, decks, 3D games, reports, dashboards and galleries. Artifacts on Fly
'a corollary is that information about product quality will become more important and impactful' This feels like the next evolution of SEO/AEO that every product will try to game. Even if agents do th
Recommended paper from Sakana AI on recursive self-improvement. They propose an interesting way to scale recursive self-improvement through multi-agent self-supervision. In this line of research, self
arXiv:2603.08706v2 Announce Type: replace Abstract: Imitation learning (IL) teaches language-model agents to reproduce expert actions but not to distinguish them from plausible mistakes. Self-reflecti
arXiv:2610.11552v1 Announce Type: new Abstract: Large language model agents can invoke tools fluently, but enterprise workflows demand more than selecting the right tools: actions must strictly comply
arXiv:2610.10812v1 Announce Type: new Abstract: Small language models (SLMs) have been increasingly adopted for onboard robot operation because they enable intelligent decision-making. However, existi
Eli Tan / New York Times: Sources detail Mark Zuckerberg's decision to launch Muse despite safety concerns, after seeing that AI startup Instinct's similar agent product gained traction — Meta had del
arXiv:2610.10087v1 Announce Type: new Abstract: Offline MARL increasingly relies on generative policies to model multimodal joint behavior, typically by distilling a centralized teacher into decentral
arXiv:2610.07587v1 Announce Type: new Abstract: LLM orchestration investigates how an orchestrator coordinates a group of autonomous agents to achieve common goals or maximize collective welfare. The
arXiv:2610.07886v1 Announce Type: new Abstract: Dietary nutrition planning plays an important role in chronic disease management and maintaining a healthy body. In applications, it must simultaneously
arXiv:2610.06852v1 Announce Type: new Abstract: Pipeline figures in ML papers must be repurposed across many canvases, including paper columns, 16:9 slides, portrait posters, 1:1 social teasers, 9:16
arXiv:2610.05961v1 Announce Type: new Abstract: Valuing player actions in football requires accounting for strategic interactions among 22 players, including off-ball movements and defensive positioni
Across the public sector, the question has shifted from “what’s possible?” to “how can we drive mission impact?” We’ll be answering this question at the Google Public Sector Summit on October 20th at
SemiAnalysis: Analysis: Anthropic's subscriptions offer ~5x more API-equivalent value per month than OpenAI's for agentic workloads with Claude Opus 5.5 vs. GPT-6.1 Sol — Limit testing every AI subscr
Today, we’re announcing Google Cloud Modernize, an end-to-end transformation portfolio to help enterprises collapse multi-year roadmaps with the power of AI. Google Cloud Modernize brings together Goo
arXiv:2610.02710v1 Announce Type: cross Abstract: Terminal agents are increasingly deployed beyond software engineering in science and other specialized domains. Constructing training environments req
I agree that chatgpt/codex has the current best agent interface for deep work. - It unifies all my work (coding/knowledge work) in one interface. Toggling between chatgpt/codex doesn't have explicitly
Agentic AI is changing the identity security equation. Enterprises are no longer governing access only for employees and traditional machine identities. AI agents can act on behalf of people, interact
Learn to build a custom harness, folks. Mods in Claude Code, DeepSeek Harness, and now Pi Durable. What do these all have in common? Increased extensibility. Builders need coding agents and harnesses
arXiv:2610.00025v1 Announce Type: new Abstract: Agent harnesses increasingly want to run small language models (SLMs) on the microtasks around a frontier large language model (LLM) planner: auto-appro
arXiv:2610.01614v1 Announce Type: new Abstract: Generative video world models can now synthesize open-ended environments that agents can navigate and interact with in simple ways. Yet open-ended gener
Recursive Language Models: Claude Code, Agent Swarms, Big Research Bets, & the $40M AI Problem Solver https://www.latent.space/p/rlm MIT’s @a1zhang explains why Claude Code, Codex, and Pi are basicall
The BEA's new Q2 GDP-by-state was released, but the key data is entirely in an infographic, without a text-layer. LlamaParse's agentic parsing tier understands documents like this by default, and fait
arXiv:2609.39066v1 Announce Type: new Abstract: Conventional image forgery detection methods produce binary scores or pixel-level masks without interpretable evidence, while recent multimodal large la
arXiv:2609.39135v1 Announce Type: new Abstract: Physical reasoning from video requires inferring latent physical properties and dynamics beyond direct observation. Direct VLM inference remains unrelia
arXiv:2609.39392v1 Announce Type: new Abstract: Autonomous research agents can generate hypotheses and conduct experiments, but experimentation remains a major source of computational cost. A fundamen
arXiv:2609.38982v1 Announce Type: cross Abstract: Coding agents powered by large language models (LLMs) have shown remarkable abilities to autonomously reason about and achieve goals in the digital wo
Carl Franzen / VentureBeat: Strands Labs, AWS's experimental agent-development project, unveils Strands Decider 2B, a free, open-source Jev competitor fine-tuned from an Alibaba Qwen base — The race t
arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations ty
arXiv:2609.38753v1 Announce Type: cross Abstract: Companion agents describe themselves: they remember, they understand their users, the relationship has changed them. We argue that such accounts, and
arXiv:2609.34603v2 Announce Type: replace Abstract: Does repairing an episode make its experience a better memory for the next task? We transfer the same failed source before and after accepted repair
arXiv:2609.36505v1 Announce Type: new Abstract: Agentic reinforcement learning (ARL) with verifiable rewards improves the ability of large language models (LLMs) to tackle knowledge-intensive tasks by
arXiv:2609.37567v1 Announce Type: cross Abstract: Driven by the rapid advancement of large language models (LLMs), LLM-based multi-agent systems (MAS) have emerged as a powerful paradigm for collabora
arXiv:2609.37226v1 Announce Type: cross Abstract: Answering questions and completing tasks over large document collections often requires connecting evidence spread across multiple documents, such as
arXiv:2609.37454v1 Announce Type: new Abstract: Underwriters in commercial Property and Casualty (P&C) insurance spend 30 to 40% of their time on administrative work rather than risk judgment, and a s
Casey Newton / Platformer: Hands-on with Dots, OpenAI's work-focused agentic product: highly capable and intuitive, with natural-feeling conversations represented as a chat inside ChatGPT — With safet
arXiv:2609.37544v1 Announce Type: new Abstract: Content-generation agents continuously receive impressions, clicks, conversions, and negative feedback from recommendation systems, providing real-world
arXiv:2609.37834v1 Announce Type: new Abstract: Harness optimization provides a practical setting for recursive self-improvement (RSI), where agent-generated modifications inform subsequent changes th
arXiv:2609.32490v2 Announce Type: replace Abstract: LLM-based multi-agent systems (MASs) have shown strong potential for solving complex tasks, but most assume that task requirements are sufficiently
arXiv:2609.38024v1 Announce Type: new Abstract: An agent skill is a reusable, actionable natural-language artifact that guides an agent to perform a task effectively under a given harness. Recent stud
🚨🔥 Congress (@RepJoshG @ValerieFoushee @tedlieu) to OpenAI, Anthropic, Google, Meta, SpaceX on their inadequate reporting of their inadequately-controlled agents: “Your companies have since notified t
arXiv:2609.31715v1 Announce Type: new Abstract: Agentic recognition requires visual perception to move beyond static scene understanding and produce structured scene representations that support the p
arXiv:2609.32213v1 Announce Type: new Abstract: Agent performance depends on both the underlying model and the harness that manages its tool use and execution. Selecting a suitable pair requires accou
Every major security shift ultimately comes down to one question: Who or what is allowed to do this? For most of the past two decades, the answer was a person with a username and password. In the arti
arXiv:2609.35058v1 Announce Type: new Abstract: Effective multi-turn agents require interaction strategies that coordinate information gathering, actions, and feedback over long horizons. GRPO is a re
arXiv:2609.31326v1 Announce Type: cross Abstract: Ordinal acne severity grading requires distinguishing visually similar neighboring grades while jointly weighing holistic facial appearance and locali
arXiv:2609.30863v1 Announce Type: cross Abstract: The emergence of AI agents is expected to reshape software engineering by moving beyond AI as assistants towards systems capable of planning, executin
Only an open ecosystem can guarantee the safety of AI Today, with over 100 industry partners, we introduced the NVIDIA Open Agent Safety Platform, bringing together OpenShell and Sentry. Artificial in