Knowledge catalogue
Today on TITV: -Trump asks OpenAI to stagger release of new model | @leomschwartz & @amir, The Information -Google pressures publishers on AI licensing | @anngehan -Inside an AI power user’s agent wor
arXiv:2606.25527v1 Announce Type: new Abstract: Online reinforcement learning (RL) agents increasingly depend on knowledge acquired offline to achieve practical efficiency. Originally studied in offli
Incident response company BreachRx Inc. today launched the Rex Platform, an agentic artificial intelligence incident command center built for a future in which AI-accelerated attacks set off several b
arXiv:2604.25496v2 Announce Type: replace Abstract: Offline zero-shot reinforcement learning (RL) aims to learn agents that optimize unseen reward functions without additional environment interaction.
arXiv:2606.25497v1 Announce Type: new Abstract: Object-Goal Navigation (ObjNav) requires embodied agents to autonomously locate specified targets using only egocentric visual observations. Existing mo
arXiv:2606.25535v1 Announce Type: new Abstract: Quantitative maps from dynamic contrast-enhanced MRI (DCE-MRI) are essential for tumor assessment but are often unavailable due to contrast-agent risks
arXiv:2606.25880v1 Announce Type: new Abstract: Embodied Visual Tracking (EVT) requires an agent to continuously follow a specified target while actively moving through dynamic environments. However,
arXiv:2606.26027v1 Announce Type: new Abstract: Tool use enables large language models (LLMs) to perform complex tasks, and recent agentic reinforcement learning (RL) methods show promise for enhancin
arXiv:2606.25964v1 Announce Type: cross Abstract: Small (sim2B) GUI-grounding agents are attractive for on-device deployment, accessibility tooling, and low-cost iteration, but at this scale they face
Decisions about how to use AI in your organization are increasingly organizational design and strategy decisions, not IT choices: How do you integrate agents into your firm? What intelligence will you
arXiv:2606.23993v1 Announce Type: cross Abstract: High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (extit{triggering}) under tight constraint
arXiv:2601.18747v2 Announce Type: replace-cross Abstract: Modern AI agents increasingly rely on search infrastructure to execute complex, neuro-symbolic reasoning workflows. These workflows often comp
The conversations at last week’s AWS Summit NYC 2026 showed that AI evolution is entering a new phase. From physical robots tackling labor shortages to agentic systems reshaping enterprise operations,
arXiv:2606.21775v1 Announce Type: new Abstract: Recently, world models have emerged as a promising paradigm for building intelligent agents by learning predictive models that estimate future environme
arXiv:2606.23521v1 Announce Type: cross Abstract: Long-running LLM agents keep valuable state resident on GPUs: KV caches, request schedulers, communication state, and sometimes online adapters. Losin
arXiv:2606.21496v1 Announce Type: cross Abstract: Deploying generalist robotic agents in the real world requires transferable skills. Specifically, a policy trained to clone a behavior from object-spe
arXiv:2606.20658v1 Announce Type: cross Abstract: Planning under uncertainty requires agents to balance goal achievement with information gathering. Active inference addresses this through the Expecte
arXiv:2602.06776v2 Announce Type: replace-cross Abstract: We study the transit stop placement (TrSP) problem in general metric spaces, where agents travel between source-destination pairs and may eith
arXiv:2606.22424v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to follow natural-language instructions in unseen scenes. While Large
arXiv:2606.21097v1 Announce Type: cross Abstract: Deploying highly capable personalized conversational agents in resource-constrained or privacy-sensitive environments remains a significant challenge.
arXiv:2606.21136v1 Announce Type: new Abstract: Learning accurate value functions plays a decisive role for reinforcement learning (RL) agents to solve long-horizon, complex tasks. Conventional tempor
arXiv:2606.20999v1 Announce Type: cross Abstract: Understanding the generalization capabilities of visuomotor policies is essential in the development of capable robotic agents. Generalizable models l
arXiv:2606.23296v1 Announce Type: new Abstract: Developing generalist embodied agents requires interactive environments providing visually realistic feedback and accurate action-conditioned dynamics.
arXiv:2506.02849v3 Announce Type: replace-cross Abstract: In this letter we study 1v1 quadrotor pursuit-evasion, where a pursuer and an evader are trained via reinforcement learning (RL) by competing
Live Stream: Welcome to open source AI Lots of new folk are starting out on their journey with open models. Come join our livestream with all your questions about local models, open coding agents, and
arXiv:2606.22296v1 Announce Type: new Abstract: Edge Internet of Things (IoT) agents are often constrained by memory capacity, privacy requirements, communication latency, and recurring inference cost
In this post, you will learn patterns for implementing production-ready multi-tenant systems using Amazon Bedrock AgentCore. You will see these patterns demonstrated through healthcare AI agents that
arXiv:2606.18697v2 Announce Type: replace Abstract: Model-based learning agents use learned world models to predict future states, plan actions, and adapt to new environments. However, the process of
Another new idea to push the state of AI architectures forward. Sakana released a model that effectively uses a mixture of models to get work done. You get a single API but then the work gets farmed o
The next era of AI will not be defined by compute alone. Its growth will be determined by energy. As accelerated computing scales across AI factories, agentic AI, industrial AI, edge computing and phy
GLM 5.2 x AWS GLM-5.2 is accessible via http://Z.ai GLM API on AWS Marketplace 🚀 Powerful long-horizon autonomous workflows, top-tier coding & multi-step agent reasoning capability, delivered through
Grok Build upgrades /goal is live on Grok Build. We use a team of agents: - implementors - skeptics - code reviewers - planners and a mix of grok build and composer in various roles. Would love to hea
The Top AI Papers of the Week (June 14 - June 21): - PreAct - SpatialClaw - Back on Track - OpenClaw-Skill - From Trainee to Trainer - Compositional Skill Routing - Can LLM Agents Infer World Models?
GLM 5.2 quantized GGUFs: https://huggingface.co/unsloth/GLM-5.2-GGUF GLM 5.2 on Open Router: https://openrouter.ai/z-ai/glm-5.2 Minion coding agent: https://github.com/Sentdex/minion A decent consolid
The real valuable capability MCP offers over skills/CLI is isolating the auth flow outside of the agent’s context window, and potentially out of the harness completely. [...] Maybe the idealized form
This is what the AI engineering ecosystem looks like in one room. 60+ Gold Sponsors are joining us at AI Engineer World's Fair, spanning infra, inference, agents, data, eval, and observability. The wh
arXiv:2606.11634v1 Announce Type: new Abstract: The rapid progress of reasoning and agentic large language models (LLMs) has increased the demand for long-context inference, but self-attention (SA) sc
arXiv:2606.12411v1 Announce Type: new Abstract: Modern conversational agents condition on an ever-growing dialogue history at each turn, incurring redundant attention and encoding costs that grow with
arXiv:2601.04203v2 Announce Type: replace Abstract: We present FronTalk, a benchmark for front-end code generation that pioneers the study of a unique interaction dynamic: conversational code generati
arXiv:2509.11548v2 Announce Type: replace Abstract: Graphical user interface (GUI) grounding is a fundamental task for building GUI agents. However, general vision-language models (VLMs) struggle with
arXiv:2602.05746v2 Announce Type: replace-cross Abstract: Prompt injection is a critical vulnerability in LLM agents, yet the strongest methods still rely on human red-teamers and hand-crafted prompts
arXiv:2606.11724v1 Announce Type: new Abstract: Theory of Mind (ToM) reasoning requires inferring agents' beliefs from partial and asymmetric observations, which remains an open challenge for LLMs. Ex
arXiv:2511.13207v2 Announce Type: replace-cross Abstract: Object navigation in unseen indoor environments requires agents to perform semantic search under partial observability. Vision-language models
arXiv:2606.11637v1 Announce Type: new Abstract: Touch is a key modality for embodied agents to understand the physical world. Although recent work has incorporated tactile signals into language system
arXiv:2505.01458v2 Announce Type: replace-cross Abstract: Navigation and manipulation are core capabilities in Embodied AI, but training agents to perform them directly in the real world is costly, ti
arXiv:2606.10401v1 Announce Type: new Abstract: Spatial intelligence is a key frontier for multimodal large language models (MLLMs), enabling them to reason about the physical world from visual experi
Learn how @cursor_ai partnered with Together AI to deliver real-time inference for AI-powered coding in this article from @ce_zhang and @realDanFu. Cursor's in-editor agents generate code while develo
Nanocoder is an open coding agent for the terminal built by a community collective rather than a company. It allows users to bring their own model, keep code on their machine, and owe nothing to anyon
One thing I mentioned only in passing in my Fable post is that, for long running tasks, Fable starts to develop its own dialect as its many agents and tasks reinforce themselves and make Claudish lang
arXiv:2606.09890v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents capable of executing multi-step action trajectories toward a given objecti
arXiv:2606.10359v1 Announce Type: new Abstract: AI agents in supply chains face a fundamental epistemic gap: large language models (LLMs) interpret policies but lack physical grounding, while reinforc
arXiv:2606.10348v1 Announce Type: new Abstract: Object navigation requires an agent to locate a target in an unknown environment through visual observations. Existing methods typically rely on open-vo
arXiv:2510.14828v3 Announce Type: replace Abstract: Improving the reasoning capabilities of embodied agents is crucial for robots to complete complex human instructions in long-view manipulation tasks
arXiv:2606.10228v1 Announce Type: cross Abstract: Safe exploration is a prerequisite for deploying reinforcement learning (RL) agents in safety-critical domains. In this paper, we approach safe explor
arXiv:2512.12225v3 Announce Type: replace Abstract: Developing artificial agents that unify representation, memory, adaptation, and prediction remains a fundamental challenge in artificial intelligenc
Claude Fable 5, Anthropic’s latest frontier model, is now generally available on Google Cloud. This launch is the latest proof point of our ongoing commitment to bring the industry's latest models str
Observability and security platform company Datadog Inc. today unveiled more than 100 new capabilities at its annual DASH 2026 conference, headlined by a major expansion of its Bits AI agents that the
arXiv:2512.07998v2 Announce Type: replace-cross Abstract: We present DIJIT, a novel binocular robotic head expressly designed for mobile agents that behave as active observers. DIJIT's unique breadth
If you thought AI progress was slowing down, well here's the immediate answer to that. Huge jump in capability across the board. This is going to deliver major improvement in agents across almost all
arXiv:2601.21754v3 Announce Type: replace Abstract: While Large Language Models (LLMs) excel in language-based agentic tasks, their applicability to unseen, nonlinguistic environments (e.g., symbolic