self-modification
Self-modification in AI systems refers to the capability of an artificial intelligence to alter its own code, parameters, or behavior patterns without external intervention. This concept, discussed by
Knowledge catalogue
Self-modification in AI systems refers to the capability of an artificial intelligence to alter its own code, parameters, or behavior patterns without external intervention. This concept, discussed by
arXiv:2605.29440v1 Announce Type: cross Abstract: Retrieval-augmented LLM agents increasingly rely on curated skill banks: collections of reusable textual principles that guide decision making on comp
Sebastian Herrera / Fortune: Sources: Microsoft is working on an app that will include GitHub Copilot, Copilot chat, Copilot Cowork, and a new agentic workflow tool called Autopilot — Microsoft needs
Start creating agents using everyday language with LangSmith Fleet. Learn how to build no-code agents for real work. Take our free LangChain Academy course today: https://academy.langchain.com/courses
arXiv:2605.30328v1 Announce Type: new Abstract: Efficient and robust 3D scene representation is crucial in autonomous driving, robotics, and related fields. While RGB images provide valuable content f
The hand-wringing over token usage is real, but I don’t see any organization that has adopted AI retreating from use in coding or even considering it. We are a few months into agentic coding, and comp
The latest finding in the LangSmith Signal: Open Models are having a moment. 1 in 3 AI teams ran an open-weights model in April 2026, up from 1 in 5 nine months ago. The overall number of teams using
The teams seeing the biggest wins from AI are completely changing how they work, not speeding up what they already do. What steps can you delete, what handoffs go away, what can an agent just own end
Tonight, I'm having dinner with a bunch of high-performing @Rippling team members (something we do every year). So I asked Rippling AI to give me a dossier on everyone I'm seated with, and the quality
arXiv:2605.29861v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced autonomous agents from deep search, which retrieves concise factual answers, to deep research, which synthe
arXiv:2508.14610v2 Announce Type: replace Abstract: Despite extensive developments in motion planning of autonomous aerial vehicles (AAVs), existing frameworks faces the challenges of local minima and
arXiv:2605.29115v1 Announce Type: cross Abstract: Unix competence is the ability to use shell and operating-system primitives as first-class tools, not merely to write programs through a terminal. Cur
arXiv:2605.28978v1 Announce Type: new Abstract: Finite Element Analysis (FEA) serves as the cornerstone of modern engineering design. However, its workflow is inherently complex and relies heavily on
arXiv:2605.29640v1 Announce Type: new Abstract: Large Language Models have revolutionized interactive applications; however, their finite context windows pose a critical data management challenge for
arXiv:2605.30011v1 Announce Type: cross Abstract: Recent work has begun to equip vision-language-action (VLA) policies with explicit intermediate reasoning. In embodied control, however, textual chain
We comprehensively benchmarked Opus 4.8 on document understanding tasks, and compared it to Opus 4.7. It's fairly apparent that Opus 4.8 wasn't explicitly post-trained on visual document understanding
We've seen lots of enthusiasm for Devin's end-to-end testing capabilities in its virtual machine. In this post, @ido_pesok shares the technical details behind how we implement testing for verification
Worked on some code this morning using Opus 4.8 and so far I'm really liking it. Much more cooperative than 4.7 and less 'over agentic'. Stops and asks for my input when needed in places 4.7 (and GPT
arXiv:2605.29341v1 Announce Type: cross Abstract: Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving wo
3 hour turn around on custom feature request! @yoheinakajima @cura_inc okay live! custom tags / labels so you can filter as you see fit! configurable on the UI but also via MCP/AI so super easy for yo
a hot (cold at this point?) take that lead us to build this: every agent in the future will need a sandbox to connect to writing/executing code is not just for coding agents! is useful for all sorts o
A TLDR on LangSmith Sandboxes: ✅ Hardware-virtualized microVM ✅ Kernel-isolated from your services + other sandboxes. ✅ Same SDK and API key as the rest of LangSmith ✅ Any framework or custom code ✅ N
arXiv:2605.22166v2 Announce Type: replace Abstract: LLM agents are shaped not only by their language models, but also by the runtime harness that mediates observation, tool use, action execution, feed
arXiv:2605.28607v1 Announce Type: new Abstract: Modern information systems require autonomous agents capable of navigating complex workflows, yet current methodologies often struggle with the transiti
arXiv:2605.27643v1 Announce Type: new Abstract: Light-based advanced manufacturing increasingly requires programmable, closed-loop tools that translate human design intent into executable operations a
arXiv:2605.27396v1 Announce Type: cross Abstract: Autonomous AI agents now plan, decide, and act on behalf of users across healthcare, financial services, and workplace contexts, often without step-by
arXiv:2605.27575v1 Announce Type: new Abstract: As organizations move toward production deployments of AI agents, which execute non-deterministic workflows, maintain stateful sessions, and often opera
The breakneck expansion of AI is forcing enterprise IT leaders to urgently rethink how infrastructure and cyber resilience work together to protect critical assets. Above all else, securing foundation
arXiv:2605.27905v1 Announce Type: new Abstract: AI research agents can now generate research ideas, design experiments, run code, and draft papers, raising the possibility of large-scale AI-assisted s
arXiv:2605.27873v1 Announce Type: new Abstract: AI models underpin data-centric applications from image and text processing to scientific discovery in biology, physics, and chemistry. Yet developing t
arXiv:2605.28666v1 Announce Type: new Abstract: In modern industry, dynamic environments and the complexity of modular and reconfigurable resources require automated planning of process sequences. Cap
arXiv:2605.28092v1 Announce Type: new Abstract: Signal Temporal Logic (STL), has recently seen extensive development, owing to its rich expressivenes for autonomous planning and control. Nevertheless,
As agent harnesses become more standardized, we’re going to see a lot more “managed agent services” Managed Deep Agents lets you create a managed Deep Agent without standing up a custom agent server.
Russell Brandom / TechCrunch: Asana acquires StackAI, a no-code platform for building AI agents, for 75M as part of Asana's broader AI pivot; PitchBook: StackAI raised ~20M — Asana has acquired the wo
Work management software company Asana Inc. today said it has completed the acquisition of StackAI Inc., a no-code platform for building artificial intelligence agents, in a deal that adds the ability
arXiv:2605.28287v1 Announce Type: new Abstract: Discovering novel stable molecules without training data remains a grand scientific challenge. Current molecular generative models are trained on large,
This post demonstrates that integration in action by automating one of the most labor-intensive workflows in financial services: anti-money laundering (AML) alert triage. You will build a triage workf
arXiv:2605.28655v1 Announce Type: new Abstract: Scientific research proceeds through iterative cycles of hypothesis generation, experiment design, execution, and revision. AI agents can automate parts
Harrison Chase shared a positive experience attending Boston Tech Week and highlighted interaction with Blitzy AI. The post captures participation in a technology industry event in Boston and engageme
arXiv:2605.28807v1 Announce Type: new Abstract: Agentic AI systems capable of autonomous planning and extended environmental interaction pose a fundamental control problem: how can humans maintain mea
arXiv:2605.27706v1 Announce Type: new Abstract: We introduce CAROL (Chain-based Adaptive Reconfiguration Over Lattices), a probabilistic framework for test-time hallucination reduction in large langua
arXiv:2601.04505v3 Announce Type: replace Abstract: Generating accurate circuit schematics from high-level natural language descriptions remains a persistent challenge in electronic design automation
arXiv:2603.00349v2 Announce Type: replace Abstract: Many complex tasks require extended effort, diverse capabilities, or coordinated actions beyond what a single agent can provide. However, simply add
Artificial intelligence cloud operator CoreWeave Inc. today announced the launch of a new offering that gives enterprise outfits the ability to deploy AI agents that can learn and improve themselves a
arXiv:2605.27954v1 Announce Type: new Abstract: Agentic large language models are increasingly used to solve real-world tasks by reasoning over goals, invoking tools, and interacting with external env
arXiv:2605.28104v1 Announce Type: new Abstract: Recent years have witnessed the rapid development of Large Language Model-based Multi-Agent Systems (MAS), which excel at collaborative decision-making
arXiv:2605.28148v1 Announce Type: cross Abstract: The rapid development of LLMs coupled with the introduction of Model Context Protocol (MCP) has revolutionized how intelligent agents interact with AP
Deploying a Hermes Agent with Fly, Modal, OpenRouter, & Cloudflare 02:43 Managed vs VPS 06:08 Architecture 15:14 Setup 22:23 Deployment 28:00 Access / OIDC 39:57 Hermes and Open WebUI 52:07 Cloudflare
arXiv:2605.27470v1 Announce Type: cross Abstract: Graph anomaly detection aims to identify anomaly nodes in attributed graphs and plays an important role in real-world applications. However, existing
arXiv:2603.00309v2 Announce Type: replace Abstract: The increasingly popular agentic AI paradigm promises to harness the power of multiple, general-purpose large language model (LLM) agents to collabo
arXiv:2605.27571v1 Announce Type: new Abstract: Modern analytics systems are fundamentally reactive, requiring users to define queries over increasingly complex and continuously evolving data. In real
arXiv:2605.28532v1 Announce Type: new Abstract: Tool-using agents often incur substantial computational cost due to long reasoning chains and iterative tool usage. In practical scenarios, many tasks b
arXiv:2605.28787v1 Announce Type: cross Abstract: In the era of autonomous agents, machine-actionable data is critical for data-driven workflows. For more than a decade, semantic metadata like schema.
arXiv:2307.06240v2 Announce Type: replace-cross Abstract: The Drone Swarm Search project is an environment, based on extsc{PettingZoo}, that is to be used in conjunction with multi-agent (or single-ag
arXiv:2605.27428v1 Announce Type: new Abstract: Edge deployments of generative inference increasingly face two practical realities: per-device per-model performance is often unknown at deployment time
Evals shape agent behavior. Every eval is a vector that shifts the behavior of your agentic system. More evals ≠ better agents. Instead, build targeted evals that reflect desired behaviors in producti
This post combines learnings from LangChain’s work on evaluating deep agents and Anthropic’s guide to demystifying evals for AI agents into a practical guide. In this post, you will learn how to: 1) a
arXiv:2605.28751v1 Announce Type: cross Abstract: Linear interpolation between fine-tuned checkpoints has been shown to trace the Pareto front between competing objectives, but whether extrapolative w
arXiv:2510.06970v2 Announce Type: replace-cross Abstract: Compliance with maritime traffic rules is essential for the safe operation of autonomous vessels, yet training reinforcement learning (RL) age
arXiv:2605.27651v1 Announce Type: new Abstract: Autonomous space systems operating in extreme thermal environments require accurate and efficient thermal modeling to support both pre-mission system de