agents

Wake up, people! What we should actually fear, near term, is not so much rogue superintelligence as unleashed agentic AI hacking the internet at scale: “[If you have enough money], you can now instruc

arXiv:2609.19182v1 Announce Type: new Abstract: Benchmarks are central to how progress in large language models (LLMs) is assessed and communicated. Yet model rankings alone reveal little about how ev

Enterprises are moving beyond standalone AI tools as they look for ways to weave agents into the work employees and customers already do. The shift toward connected AI workflows raises broader questio

arXiv:2609.20480v1 Announce Type: new Abstract: Occlusion creates fundamental uncertainty in autonomous driving. Existing methods often propagate frame-wise hypotheses or optimize ego behavior against

Wow, check out this DuckTales theme as a three-voice fugue in the style of Bach's Well-Tempered Clavier. My AI music theory system, which consists of a Rust CLI tool called mtdt and an agent skill lib

arXiv:2609.19393v1 Announce Type: new Abstract: Work zones alter lane geometry through temporary traffic controls and closures that may be absent from on-board maps, challenging autonomous vehicle (AV

A database knows where your data is. A vector database understands what your data means. It finds information based on similarity and meaning, not just exact keywords, powering semantic search, RAG, r

Wood Mackenzie built APEX, a shared agentic AI platform on Amazon Bedrock AgentCore so every team can ship production agents without rebuilding runtime, identity, observability, and guardrails from sc

arXiv:2609.18298v1 Announce Type: cross Abstract: Agentic-AI based software development offers the promise of faster completion of the software, greater programmer efficiency, and more reliable code.

arXiv:2609.18542v1 Announce Type: new Abstract: 4D radar has emerged as a promising next-generation sensor for improving the robustness of autonomous driving perception systems because of its stable s

arXiv:2609.18738v1 Announce Type: new Abstract: Automating robotic harvesting in intensive agriculture within Mediterranean greenhouses requires overcoming significant challenges related to the geomet

arXiv:2609.19125v1 Announce Type: cross Abstract: Computer-use agents increasingly operate software designed for people, but interfaces often leave actions or task state unclear to machine readers. We

arXiv:2601.00743v2 Announce Type: replace Abstract: Integrating symbolic constraints into deep learning models could make them more robust, interpretable, and data-efficient. Still, it remains a time-

Dwarkesh Patel / Dwarkesh Podcast: An interview with OpenAI researcher Noam Brown about multi-agent systems, AI solving the Navier-Stokes problem, the internal/external model gap, and more — “We never

arXiv:2609.18881v1 Announce Type: new Abstract: First-person-view (FPV) teleoperation of aerial swarms requires an operator to coordinate collective translation, viewing direction, and formation spaci

arXiv:2609.18779v1 Announce Type: new Abstract: Current Mixture-of-Agents (MoA) paradigms generally treat query routing and agent fine-tuning as separate processes, limiting their ability to respond t

arXiv:2609.18950v1 Announce Type: new Abstract: A robot's learned model of its own dynamics is only valid until those dynamics change: actuators wear, payloads shift, and joints stiffen. A model-based

arXiv:2609.18051v1 Announce Type: new Abstract: Fresh-market blueberries require selective, gentle picking, which is labor-intensive and expensive. Over-the-row machine harvesters are fast but non-sel

Why evaluating image editing models is both critical and challenging Instruction-based image editing is becoming a core capability of multimodal foundation models. Users can increasingly edit images s

arXiv:2609.19128v1 Announce Type: new Abstract: Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery fro

arXiv:2609.17921v1 Announce Type: new Abstract: Vision-language model (VLM) agents combine specialized perception, tools, and reasoning to address complex visual tasks. In multi-agent settings, differ

arXiv:2609.17697v1 Announce Type: new Abstract: Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining

arXiv:2609.17708v1 Announce Type: cross Abstract: Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that

arXiv:2609.17601v1 Announce Type: cross Abstract: This paper studies decentralized learning of socially optimal equilibria in finite normal-form games over dynamic communication networks. Each agent o

arXiv:2609.18620v1 Announce Type: new Abstract: Creating deformable assets for robot manipulation requires jointly specifying their geometry, appearance, and physical properties. This is especially ch

arXiv:2609.18417v1 Announce Type: new Abstract: Multi-turn agent trajectories often contain redundant rounds (failed tool calls, parallel sub-queries, verification-only steps) that inflate both traini

arXiv:2609.17590v1 Announce Type: cross Abstract: Evolutionary Ensemble Search (EES) constructs machine-learning procedures through expert-guided program evolution. A role-specialized council turns ta

arXiv:2608.28363v2 Announce Type: replace Abstract: LLM agents increasingly modify their own prompts, tools, middleware, resources, and execution harnesses at runtime. Such self-evolution can improve

arXiv:2609.18238v1 Announce Type: new Abstract: Observational decision-support systems often expose one causal estimate as a recommendation even when plausible estimators disagree. The inherent engine

arXiv:2609.18346v1 Announce Type: new Abstract: Large language models (LLM) deployed as autonomous pricing agents may sustain supracompetitive prices through tacit coordination. We develop a causal gr

arXiv:2609.18058v1 Announce Type: new Abstract: Finding the object referred to by language in a partially observed 3D scene is a core capability for embodied agents. Existing approaches either couple

Google announced “CC,” an experimental AI agent that extends the Gemini‑powered personalization available in Google’s ecosystem to whole families of up to six members. Each family can grant limited ac

Google LLC today opened its experimental artificial intelligence agent CC to families, with as many as six people in a household able to share one. Each member picks what the agent is allowed to see,

arXiv:2609.17771v1 Announce Type: cross Abstract: Approaches to incorporating human awareness into mobile robot decision-making mainly focus on collision avoidance in low-level motion planning, often

Evals measure failures you know how to name. Arize Signal continuously reviews production traces to find recurring trajectory failures you do not, then turns them into evidence for tests and fixes. Th

How To Write With An LLM Thomas Ptacek on using LLMs as copyeditors, not as writing assistants: Rule Number One: You may not use a single word an LLM suggests to you. [...] I think that as a form of i

arXiv:2609.18598v1 Announce Type: cross Abstract: Self-driving laboratories can explore synthesis conditions autonomously, but their decision-making layer is typically a black-box optimizer, and the o

Learn how to enforce defense-in-depth authorization for Model Context Protocol (MCP) tools on Amazon Quick. This walkthrough wires Microsoft Entra ID group and claims-based JWTs through an Amazon Bedr

arXiv:2609.17856v1 Announce Type: cross Abstract: Heterogeneous cooperative perception (CP) enables connected vehicles with diverse sensor setups to share spatial awareness via compact feature maps, w

It was great to be at Connected Stack last week with founders and builders working on what’s next in enterprise AI. @jerryjliu0 joined the Founder Flash Talks to talk about a problem every enterprise

arXiv:2609.18955v1 Announce Type: new Abstract: Efficient perception models are essential for real-time autonomous driving, where accuracy and computational cost must be carefully balanced. However, a

arXiv:2609.17628v1 Announce Type: new Abstract: Active perception allows autonomous agents to select their viewpoints rather than passively process the viewpoints given to them, enabling them to targe

arXiv:2509.12151v3 Announce Type: replace-cross Abstract: We present a learnable physics-based model that predicts motion of the robot end effector and reaction force-torque in contact-rich manipulati

arXiv:2609.18511v1 Announce Type: cross Abstract: In autonomous driving, perception models often struggle to generalize to new environments due to domain shifts. While unsupervised model adaptation of

arXiv:2609.18445v1 Announce Type: new Abstract: Agent skills, reusable procedural documents that extend LLM agents beyond their parametric memory, have become an important interface for deploying agen

arXiv:2609.18357v1 Announce Type: new Abstract: Large language model (LLM) pricing agents may respond to how market data is presented, even when its numerical values remain unchanged. We introduce mar