Search: “agents”

This might be the most important score your website will ever get. Agents are about to become the #1 source of traffic on the internet. Sites that aren't ready will disappear. http://orank.ai spawns r

arXiv:2511.09149v4 Announce Type: replace Abstract: While natural language is the de facto communication medium for LLM-based agents, it presents a fundamental constraint. The process of downsampling

Certinia Inc. wants to transform the professional services industry with artificial intelligence — tasking teams of AI agents to work alongside employees. The company operates a Salesforce-native clou

communication is hard! structured outputs make its more clear how subagents should communicate back to the main agent deepagents now supports structured output for subagents! an under appreciated piec

This post is cowritten by Renata Salvador Grande, Gabriel Bueno and Paulo Laurentys at Rede Mater Dei de Saúde. The growing adoption of multi-agent AI systems is redefining critical operations in heal

arXiv:2603.01692v3 Announce Type: replace-cross Abstract: LLM-based agents for machine learning engineering (MLE) predominantly rely on tree search, a form of gradient-free optimization that uses scal

arXiv:2604.07927v2 Announce Type: replace Abstract: Deep research requires reasoning over web evidence to answer open-ended questions, and it is a core capability for AI agents. Yet many deep research

Let me break down exactly how long it takes me to teach people AI agents. ⏱️Give business professionals their first big wow moment in under 2 minutes ⏱️Teach them meaningful use in under 17 ⏱️Teach th

memory is just context -> the harness decides what gets remembered, how, and when memory ownership = agent ownership deepagents lets you own your memory: agent-scoped, user-scoped, or org-level, all i

**deepagents** (github.com/langchain-ai/deepagents) is an open-source, MIT-licensed agent harness built on LangChain and LangGraph, equipped with built-in task planning, a filesystem backend, subag...

Vercel's open-source Knowledge Agent Template enables developers to build AI knowledge agents using a filesystem and bash tools (grep, find, cat) instead of the traditional vector database, embeddi...

arXiv:2604.06240v1 Announce Type: cross Abstract: Verifying the success of computer use agent (CUA) trajectories is a critical challenge: without reliable verification, neither evaluation nor training

arXiv:2604.06367v1 Announce Type: cross Abstract: Web agents automate browser tasks, ranging from simple form completion to complex workflows like ordering groceries. While current benchmarks evaluate

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

The specific X (Twitter) post at the provided URL could not be retrieved — the content is not publicly indexed in search results, and direct access to X posts requires authentication or is otherwis...

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

🎙️Introducing Max Agency Max Agency is a new podcast where we go deep on how the best agents are actually being built: architecture decisions, tradeoffs, evals, and everything in between. Each episode

arXiv:2610.21755v1 Announce Type: new Abstract: Large Language Model agents operate through closed-loop action policies whose decision space is defined by an agent harness. We investigate how this ope

arXiv:2610.21424v1 Announce Type: new Abstract: Scientific agents must connect research problems, methods, and findings dispersed through narrative articles. We introduce SPRA (Structured Paper Repres

arXiv:2610.21739v1 Announce Type: cross Abstract: As agents powered by foundation models move into open-ended environments, continual learning from experience becomes essential. For agents built on mo

arXiv:2610.21463v1 Announce Type: cross Abstract: Large language model agents solve tasks through long sequences of tool calls, and the prevailing design has a single strong model generate every step,

arXiv:2610.17710v1 Announce Type: new Abstract: Training graphical user interface (GUI) agents with reinforcement learning suffers from sparse outcome rewards, leading to inefficient learning. Process

arXiv:2610.19159v1 Announce Type: cross Abstract: Can AI agents carry out research on open scientific problems? We introduce Into the Unknown, a benchmark that provides an agent with a science paper a

arXiv:2610.15582v1 Announce Type: new Abstract: We study the problem of inverse garment design, reconstructing simulation-ready 3D outfits with arbitrary layers from a single image, with visual agents

arXiv:2610.15390v1 Announce Type: cross Abstract: Audio Large Language Models (Audio LLMs) are embedded in agents for smart homes, vehicles, wearables, and embodied systems, where acoustic inputs can

arXiv:2610.14350v1 Announce Type: cross Abstract: Having demonstrated a strong potential for automating vulnerability discovery, AI agents can also be used to attack software systems at scale. Today's

More AI agents will soon be able to browse and purchase from Shopify listings, marking an expansion of the company's agentic commerce ambitions. Shopify announced Tuesday it will let shoppers configur

arXiv:2610.13335v1 Announce Type: new Abstract: Tool-using agents increasingly require a common substrate for building, training, evaluating, distilling, and maintaining agentic systems, yet existing

arXiv:2610.13064v1 Announce Type: new Abstract: Large Language Model (LLM) agents have demonstrated remarkable capabilities in tackling complex tasks through agentic workflows. However, manually desig

arXiv:2606.16215v2 Announce Type: replace-cross Abstract: Multi-turn tool-use agents must reason, call tools, and adapt to observations across several interaction turns. Post-training such agents is c

arXiv:2610.12651v1 Announce Type: new Abstract: LLM agents executing multi-step workflows fail in two fundamentally different ways: recoverable slips, which further attempts can repair, and knowledge

Banger paper from Meta Superintelligence Labs on self-improving agents. (bookmark it) It's hard to know exactly what drives self-improvement, since so many variables are at play (notes, skills, tool c

Super interesting NVIDIA paper on choosing base models for coding agents. It's actually a clever way to rank base checkpoints by how well each one is likely to do as a coding agent after post-training

arXiv:2512.11147v2 Announce Type: replace-cross Abstract: AI agents are increasingly granted autonomous access to sensitive user data and third-party services, making effective permission management a

arXiv:2610.08082v1 Announce Type: new Abstract: LLM tool-use agents operate in dynamic environments where many actions carry operational risk. However, most safety mechanisms react only after errors m

arXiv:2610.06514v1 Announce Type: cross Abstract: The growing adoption of large language model (LLM) agents creates a need for network administrators and security teams to audit agent behavior within

arXiv:2610.04800v1 Announce Type: cross Abstract: Graphical consoles offer a practical interface for medical acquisition assistance, allowing agents to work through the controls and visual feedback us

Banger paper from Microsoft and colleagues. If you run agents that search a large document collection, this one is worth your time. (bookmark it) They introduce CorpusMap, which resolves recurring ent

arXiv:2610.02654v1 Announce Type: new Abstract: Models of social contagion usually assume how individuals adopt beliefs and derive population behavior from it. We instead empirically measure belief ad

arXiv:2610.03020v1 Announce Type: new Abstract: Long-term agents must remember not only what is true about a user, but also how a particular agent should work with that user as their shared history ev

Great overview of context compression in LLM Agents And one interesting, unexpected finding. If your compaction policy is tuned to cut tokens, it may be making your agent run slower. Great study from

arXiv:2610.02459v1 Announce Type: new Abstract: Coding agents are extending their reach into the physical world by writing and executing robot control programs. One might expect the agents to use the

arXiv:2610.02569v1 Announce Type: cross Abstract: Coding agents have become increasingly long-horizon, autonomous, reliant on general-purpose shell and maintain their own persistent memory for self-im

arXiv:2610.03356v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly deployed in high-stakes settings such as industrial maintenance and equipment fault troubleshooting,

arXiv:2610.03089v1 Announce Type: cross Abstract: Modern Computer Use Agents (CUAs) directly interact with graphical user interfaces and execute third-party web tools, exposing them to indirect prompt

arXiv:2610.03195v1 Announce Type: new Abstract: As LLM agents decide on users' behalf which product to buy, which hotel to book, or which paper to cite, a preference for items from certain sources (th