agents

arXiv:2509.16136v5 Announce Type: replace Abstract: Designing effective reward functions remains a major challenge in reinforcement learning (RL), often requiring considerable human expertise and iter

arXiv:2606.08146v1 Announce Type: new Abstract: Fraud detection in payment, e-commerce, and telecommunications systems requires accuracy at the individual level, robustness under severe class imbalanc

arXiv:2606.09730v1 Announce Type: new Abstract: Large language models are increasingly expected to handle complex, long-horizon real-world tasks whose context demands can grow without bound, yet model

// Self-Harness: Harnesses That Improve Themselves // (bookmark this one) Most of the agent scaffolds we rely on today are built once and remain frozen or mostly unchanged. The harness, like the skill

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:2606.09610v1 Announce Type: cross Abstract: Cooperative object transportation is essential in numerous domains, including industrial to domestic services. A popular transportation strategy is to

arXiv:2606.09774v1 Announce Type: new Abstract: Advanced scientific simulators expose specialized input languages that turn simulation goals into executable configurations, but learning them can cost

arXiv:2606.08671v1 Announce Type: new Abstract: Agent skills extend language-model agents with task-specific procedures, scripts, and references, but the tasks and environments they target continually

arXiv:2606.08049v1 Announce Type: new Abstract: AI agents increasingly turn past experience into reusable artifacts such as code, workflows, and procedural memories. Reuse can improve efficiency, but

arXiv:2606.08710v1 Announce Type: cross Abstract: Modernization of legacy scientific codes is often necessary to keep up with the ever-evolving changes in the compute resource ecosystem. Parallelizati

arXiv:2606.07594v1 Announce Type: new Abstract: Personal AI agents must increasingly operate across APIs, shells, web surfaces, and desktop GUIs, yet many systems remain tuned to a single interface an

arXiv:2606.09350v1 Announce Type: cross Abstract: Reliable motion classification is critical for autonomous driving, as false dynamic predictions of static objects can cascade into unnecessary planner

// The Consistency Illusion // Multi-agent debate can make agents agree on the final answer while their underlying reasoning stays misaligned. This work finds that consensus on the output hides disagr

arXiv:2606.08998v1 Announce Type: new Abstract: Agentic AI systems can behave differently across runs: the same request may produce a different plan, a different tool call, a different code edit, or a

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

thought-to-image Can you believe the image on the right was generated from brain activity? We showed a person the dog image on the left for 0.5 seconds while recording brain signals. Our model, OB1, d

arXiv:2606.07697v1 Announce Type: cross Abstract: As atmospheric environmental prediction continues to improve, interpretable validation of pollution mechanisms and feedback processes has become a mai

arXiv:2606.08310v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as long-horizon agents with decision-making capacities. While LLMs can show ethical competence on

arXiv:2606.08256v1 Announce Type: new Abstract: Verifiability, attribution, and reproducibility are foundational requirements of scientific knowledge, yet current publishing infrastructure does not en

arXiv:2606.09227v1 Announce Type: cross Abstract: The convergence of the 2026 European Union Safe and Sustainable by Design (SSbD) framework, Corporate Sustainability Due Diligence Directive (CSDDD),

Devin is an AI software engineer developed by Cognition AI that automates coding tasks and assists with software development. The post appears to be a promotional announcement encouraging users to try

arXiv:2606.09268v1 Announce Type: new Abstract: Reliable robotic navigation necessitates the seamless integration of accurate global localization and dense, metric-consistent obstacle perception. A co

arXiv:2606.07649v1 Announce Type: cross Abstract: Long-form video generation requires systematic narrative planning and visual consistency that current short-clip methods cannot provide. Existing meth

arXiv:2606.09294v1 Announce Type: new Abstract: Multi-camera systems are increasingly adopted in robotics and autonomous navigation for their wide field of view, flexibility, and fault tolerance. Neve

arXiv:2606.08030v1 Announce Type: cross Abstract: Agentic tutoring systems introduce a coordination challenge: multiple agents may propose different but reasonable interventions, yet only one response

What are loops, and how do you build one? A 'loop' is the repeated process where some event or input kicks off an action. For example: 1. CI fails -> you fix it 2. CI fails again -> you fix it 3. CI p

arXiv:2606.07576v1 Announce Type: new Abstract: We present CARTOGRAPH, a verification layer for AI scientists that couples unresolved-subspace experiment steering (select), explicit ambiguity closure

arXiv:2606.08542v1 Announce Type: cross Abstract: Exploratory manipulation often turns an apparent failed attempt into the key evidence for what to do next. For example, a robot pulls a locked cabinet

One year prior to this post, o3 represented the most advanced AI agent available, marking a significant milestone in AI development. The statement reflects how rapidly AI capabilities have evolved, wi

arXiv:2606.06787v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise as tool-using agents but remain limited in long-horizon tasks that require remembering, organizing, and reusin

Agent Swarm & Instant Document Delivery Kimi will automatically coordinate 300 sub-agents to break down and execute your tasks. Delivers production-ready output in PPTX, Word, PDF, and Excel, straight

arXiv:2606.06525v1 Announce Type: cross Abstract: Large language models (LLMs) have emerged as powerful foundation models with strong reasoning capabilities across domains. Beyond reactive text genera

arXiv:2606.07513v1 Announce Type: new Abstract: Humans learn from social life. Simulating this process with LLM-powered agents represents a promising research direction, raising a natural question: wh

arXiv:2606.06815v1 Announce Type: cross Abstract: As malware illustrates a complex structure and behavior, detection of these has been a significant challenge in the domain of cybersecurity along with

arXiv:2606.07326v1 Announce Type: new Abstract: Despite being a pivotal frontier, interactive world modeling remains underexplored in terms of the versatile controllability required by practical scena

Hartley Charlton / MacRumors: Apple announces a new Foundation Models framework for developers, a new Core AI framework, and a set of Xcode enhancements aimed at agentic coding workflows — Apple today

James Pero / Gizmodo: Apple unveils an Apple Intelligence feature to automatically change compromised passwords, using agentic AI, and save them to the Passwords app — Agentic AI and security are norm

At @tryramp, engineers use Devin Desktop to bring their favorite agents into one place. With Devin Desktop they can dispatch, monitor, and jump between agents from a single surface with shared context

arXiv:2601.13508v4 Announce Type: replace-cross Abstract: Autonomous agents are beginning to transform scientific research from tool-assisted workflows toward self-sustaining discovery processes. Comp

arXiv:2512.13278v2 Announce Type: replace Abstract: Agentic reinforcement learning has advanced large language models (LLMs) to reason through long chain-of-thought trajectories while interleaving ext

@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

arXiv:2509.14380v3 Announce Type: replace Abstract: Multi-Agent Reinforcement Learning (MARL) provides a powerful framework for learning coordination in multi-agent systems. However, applying MARL to

Deep Agents are an AI concept that Sydney Runkle explains concisely in under 90 seconds, likely covering how agents can be designed to operate with deeper reasoning and decision-making capabilities. T

DeepAgents is a framework or tool designed to enable the creation of intelligent agents, likely demonstrated or explained in a brief 90-second format by Harrison Chase, a co-founder of LangChain. The

arXiv:2606.07379v1 Announce Type: cross Abstract: A growing failure mode in agent evaluation and training is that models can achieve high evaluation scores by exploiting shortcuts instead of solving t

Does a token buy you more or less now than it did a few months ago? We built a consumer price index (CPI) for AI coding output from Anthropic's Opus 4.6 model in SWE-chat, Feb 5–Apr 15, 2026. What we