Search: “agents”

The @aiDotEngineer schedule wins for having the most possible ways that developers can interact with it: JSON, llms.txt, MCP server, iCal, embeddings, agent skill https://ai.engineer/worldsfair/schedu

Had the pleasure of meeting @jerryjliu0 at a @llama_index meetup in SF. We talked about document parsing and vector search market. 🌉 DM if you wanna meet in SF. Would love to chat about search, agents

arXiv:2606.12147v1 Announce Type: new Abstract: We consider the problem of engineering autonomous intelligent agents that are capable to responsibly not comply with user requests. We argue that machin

arXiv:2606.11350v1 Announce Type: new Abstract: Retrieval-augmented generation degrades when scaled to large, heterogeneous document collections, where dense similarity loses discriminative power, and

arXiv:2606.09867v1 Announce Type: cross Abstract: Optimizing register transfer level (RTL) code is of vital importance in hardware design. Large language models (LLMs) provide new methods for the auto

first in a series of technical blogs of how we build llm infra How do you support full-text search JSON filtering over agent traces that span up to hundreds of MBs, while keeping a median (P50) latenc

i showcase 'controlled' self improvement with a novel regime-to-seam approach where failures are categorized and allowed to fix targeted areas of the agent while interesting, it's more to showcase the

Lium, a startup formerly known as Astromind, today announced the launch of an “agentic harness” that helps large language models dig into the most complex and messiest datasets. The launch comes after

my weekend hobby: self improvement research in arxiv paper #2, i tackle the last topic from paper #1: @activegraphai as an architectural affordance for self-improving agents 'Regimes: An Auditable, He

arXiv:2606.10875v1 Announce Type: new Abstract: Large language models (LLMs) rely on tool use to act as autonomous agents, yet often fail in multi-step execution due to insufficient tool-related knowl

arXiv:2606.10456v1 Announce Type: cross Abstract: AI-control monitors score individual agent actions to detect misbehavior, but real harm can be distributed across many benign-looking steps, each indi

Zscaler Inc. today unveiled a major expansion of its zero-trust SASE platform, adding an agentic framework that lets administrators manage the system through natural-language prompts and extending its

arXiv:2605.22763v2 Announce Type: replace Abstract: Large language models (LLMs) increasingly excel at mathematical reasoning, but their unreliability limits their utility in mathematics research. A m

As enterprise AI budgets hit their limits earlier each year, the pressure to fund new agentic and inference workloads without expanding total spend is forcing a fundamental rethink of infrastructure a

arXiv:2605.11484v2 Announce Type: replace Abstract: Task completion in digital and physical environments increasingly involves complex temporal interaction, where actions and observations unfold over

arXiv:2606.08450v1 Announce Type: new Abstract: Financial portfolio trading is naturally formulated as a reinforcement learning problem, where an agent sequentially rebalances assets under changing ma

arXiv:2606.09620v1 Announce Type: new Abstract: Planning collision-free motion for large robot fleets is difficult because collision avoidance induces strong inter-agent coupling that grows rapidly wi

Puffy participated in a pickleball event on June 30 in San Francisco called 'The Agent Open,' which was co-hosted with Good Friends. The event appears to have been organized or promoted through Luma,

arXiv:2606.09399v1 Announce Type: new Abstract: We present SUPERBROWSER, an autonomous web-navigation agent designed against a single guiding hypothesis: a web agent should browse the way a person bro

arXiv:2606.09236v1 Announce Type: cross Abstract: Autonomous Racing has seen remarkable progress through deep Reinforcement Learning (RL), primarily for four-wheeled vehicles. However, motorbikes intr

arXiv:2606.08021v1 Announce Type: cross Abstract: As large language model (LLM) agents are integrated into autonomous cloud operations, distributed systems face a semantic reliability problem: propose

this is sick haha. The Agent Open 🎾🏓 Everyone loves pickleball. We’re hosting a massive pickleball tournament during the AI Engineer World Fair. I’m so excited to see this event come together. This is

@cognition funny you should say that https://x.com/manuelsampedrop/status/2063746243180773656?s=20 @swyx @cognition hope it scores scope discipline too, half my agent failures are perfectly fine code

I really do think we'll see a lot of value accrue in AI startups building 'model routing as a service' Not just OpenRouter - this includes a much broader set of verticalized agents and infrastructure.

arXiv:2604.05360v2 Announce Type: replace-cross Abstract: Gait analysis is essential in post-stroke rehabilitation but remains time-intensive and cognitively demanding, especially when clinicians must

arXiv:2502.00225v4 Announce Type: replace-cross Abstract: We evaluate the ability of the current generation of large language models (LLMs) to help a decision-making agent facing an exploration-exploi

OpenAI Group PBC is still focused on its plans to transform ChatGPT into some kind of “superapp,” and it will have a heavy focus on artificial intelligence agents and autonomous coding bots, according

arXiv:2606.05646v1 Announce Type: cross Abstract: Large language models (LLMs) have enabled powerful software engineering (SE) agents capable of navigating complex codebases and resolving real-world i

arXiv:2512.20111v2 Announce Type: replace Abstract: As the time horizons of sequential decision-making tasks grow, keeping full interaction histories in model context becomes increasingly costly. Rece

Meet the winners of the Milan AI Week Hackathon. Discover how Cascade AI, ContextGuard, and Deals Machine are using agentic AI, workflow automation, and real-time orchestration on Vultr infrastructure

Building AI that Builds AI: Introducing the Sakana AI RSI Lab 🚀 https://sakana.ai/rsi-lab Today, we are announcing the Sakana AI Recursive Self-Improvement (RSI) Lab: a dedicated research group in Tok

arXiv:2606.06380v1 Announce Type: new Abstract: The question of whether artificial systems can be conscious remains open, in part because existing approaches either evaluate systems against theory-der

arXiv:2606.04746v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) algorithms are increasingly used to plan motion for robot teams in industrial warehouses and robotic shared workspaces,

arXiv:2606.04399v1 Announce Type: new Abstract: In the paradigm of decentralized learning, a group of agents collaborate to train a global model using distributed datasets without a central server. Al

arXiv:2606.05112v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed as clinical agents, yet static, single-turn benchmarks cannot capture how a model dynamically del

arXiv:2606.04029v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has received increasing attention and adoption in real-world use cases. Most of these systems follow a train-then-fix para

arXiv:2606.04433v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used in multi-image, multi-turn agentic settings where decisions depend on visual changes. However, in

arXiv:2509.08726v3 Announce Type: replace-cross Abstract: This paper focuses on the decentralized stochastic optimization problem f(mathbf{x})=frac{1}{m}sum_{i=1}^m f_i(mathbf{x}) over a connected net

arXiv:2604.17220v2 Announce Type: replace-cross Abstract: Modeling coordination among generative agents in complex multi-round decision-making presents a core challenge for AI and operations managemen

latest iteration of middleware is rad: there was a subagent that we had that was taking some pretty wild trajectories and was costing wayyyy too much We adapted a 60 line middleware from a different a

microsoft MAI tech report is a gold mine, one of the most transparent for a model at this scale. this model uses zero synthetic data or distillation from previous models. this means reasoning, agentic

arXiv:2603.03480v2 Announce Type: replace Abstract: We study reinforcement learning with delayed state observation, where the agent observes the current state after some random number of time steps. W

arXiv:2606.02754v1 Announce Type: new Abstract: Personalization is a crucial capability of modern language agents. However, current research primarily positions personalized agents as passive responde

arXiv:2606.03201v1 Announce Type: cross Abstract: Reinforcement learning from expert videos across visually distinct domains is challenging due to the absence of reward signals and the presence of dom

@swyx and I are curating the AI in GTM track at @aiDotEngineer on June 30. The thing every AI engineer must realize: GTM just became an engineering problem. Outbound = agent design. Enrichment = retri

You shipped your app. Now what? Your app may look great, but if no one can find it, it stays invisible Publishing is only the beginning Meet SEO Agent. It runs a scan for you and suggests fixes to hel