Search: “agents”

arXiv:2509.14126v2 Announce Type: replace Abstract: Collaborative transportation of cable-suspended payloads by teams of UAVs has the potential to enhance payload capacity, adapt to different payload

arXiv:2606.00197v1 Announce Type: new Abstract: Increasing interest in deep-sea operations and resources motivates the development of ecologically sensitive but environmentally durable robots. Dielect

arXiv:2606.00931v1 Announce Type: cross Abstract: Instruction-guided image editing is becoming a general interface for visual work, yet existing benchmarks still focus largely on narrow appearance edi

arXiv:2606.01091v1 Announce Type: new Abstract: Open-ended reasoning and long-form generation tasks lack reliable automatic verification signals for reward-based policy optimization. Rubrics offer a p

arXiv:2307.06647v4 Announce Type: replace-cross Abstract: We propose DeepIPCv2, an end-to-end autonomous driving framework that integrates LiDAR-based environmental perception with command-specific co

Devin Desktop runs across your entire stack, with all the integrations, capabilities, and intelligence as Devin in the cloud. Plan locally and hand off to the cloud - Devin will continue to work after

arXiv:2410.21361v2 Announce Type: replace Abstract: Domain adaptation has been extensively investigated in computer vision but still requires access to target data at the training time, which might be

Cognition AI is promoting Devin Desktop, their AI development tool, with a free download offer. Devin is an AI assistant designed to help with software development tasks, available for users to test a

arXiv:2606.00949v1 Announce Type: cross Abstract: We propose a method combining Multi-Agent Deep Reinforcement Learning (MARL) and eXplainable Deep Learning (XDL) to reduce drag in wall-bounded turbul

arXiv:2507.19881v2 Announce Type: replace-cross Abstract: Federated domain generalization has shown promising progress in image classification by enabling collaborative training across multiple client

arXiv:2510.04074v2 Announce Type: replace Abstract: Autonomous surgical systems must adapt to highly dynamic environments where tissue properties and visual cues evolve rapidly. Central to such adapta

Media Commentary is one of the most important pillars of X. And sometimes the best way to share your thoughts is with video. Today we're launching a whole new way to make them: React with Video Tap th

arXiv:2602.11554v3 Announce Type: replace-cross Abstract: How far can 3D object detection go using 4D radar alone? Despite offering weather-robust and velocity-aware sensing for autonomous perception,

arXiv:2606.00069v1 Announce Type: new Abstract: LiDAR semantic segmentation is a core perception capability for autonomous vehicles and mobile robots. However, safe operation also depends on knowing w

arXiv:2412.12036v2 Announce Type: replace Abstract: System identification, the process of deriving mathematical models of dynamical systems from observed input-output data, has undergone a paradigm sh

arXiv:2606.01198v1 Announce Type: new Abstract: Strategic classification studies settings in which agents respond to a deployed classifier by modifying observable features at a cost. Classical models

arXiv:2510.00481v2 Announce Type: replace-cross Abstract: In 2025, Large Language Model (LLM) services have launched a new feature -- AI video chat -- allowing users to interact with AI agents via rea

arXiv:2606.00471v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction is essential for safe navigation in autonomous driving and intelligent transportation systems. Despite substan

arXiv:2606.01192v1 Announce Type: new Abstract: Evaluating the performance of visual perception systems for autonomous driving is essential to ensure reliable operation across diverse environmental sc

arXiv:2603.16142v2 Announce Type: replace Abstract: Large language models (LLMs) have recently been adopted as synthetic agents for public opinion simulation, offering a promising alternative to costl

arXiv:2606.01757v1 Announce Type: new Abstract: Real-time 3D object detection is a critical component for the safe operation of autonomous driving systems and robotics. While LiDAR point clouds provid

arXiv:2602.06448v2 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based scientific agents have accelerated scientific discovery, yet they often suffer from significant inefficiencie

arXiv:2606.00970v1 Announce Type: new Abstract: We study risk-neutral control in Markov decision processes with an absorbing catastrophic state. Even though rewards are linear and the agent has no uti

arXiv:2508.19191v3 Announce Type: replace Abstract: Intraocular foreign body removal demands millimeter-level precision in confined intraocular spaces, yet existing robotic systems predominantly rely

arXiv:2606.00566v1 Announce Type: cross Abstract: As language models take on agentic roles that span calling external APIs, reading tool outputs, and acting on instructions embedded in third-party con

arXiv:2510.23057v2 Announce Type: replace-cross Abstract: We present Seq-DeepIPC, a sequential end-to-end perception-to-control model for legged robot navigation in real-world environments. Seq-DeepIP

arXiv:2606.00822v1 Announce Type: cross Abstract: Skill-based LLM agents increasingly rely on long procedural documents, but full-document prompting wastes tokens and dilutes information critical to e

arXiv:2606.00593v1 Announce Type: cross Abstract: Large language models are increasingly deployed as tool-augmented agents to acquire information beyond parametric knowledge. While recent work has imp

arXiv:2606.00762v1 Announce Type: new Abstract: Autonomous target search is crucial for deploying Micro Aerial Vehicles (MAVs) in emergency response and rescue missions. Existing approaches either foc

arXiv:2606.00825v1 Announce Type: new Abstract: AI glasses present a compelling platform for AI agents to serve as personalized memory assistants. To be genuinely useful, such systems must move beyond

arXiv:2606.01164v1 Announce Type: new Abstract: With rapid development of large language models and diffusion-based content generation, world modeling has attracted increasing research attention, bene

This is a prompt suggestion from Yohei Nakajima for analyzing ActiveGraph AI by examining its website, blog posts, and claims to produce a critical review. The post demonstrates an approach to using A

arXiv:2606.01935v1 Announce Type: new Abstract: Discrete visual tokens should provide a compact representation for both token-based world modeling and planning in autonomous driving. However, most tok

arXiv:2606.01818v1 Announce Type: new Abstract: Reliable driving scene parsing is a fundamental capability for autonomous vehicles operating in open and dynamic driving environments. However, adapting

arXiv:2606.00119v1 Announce Type: cross Abstract: Reliable work zone mapping is important for connected and autonomous vehicles (CAVs) to navigate safely and smoothly through work zone areas. Cone-mou

Verifiers are important for scaling evals/RL But costs add up! So can we make them cheaper? Some great work by @Vtrivedy10 @jakebroekhuizen in conjunction with @nikogrupen @gabepereyra and the Harvey

arXiv:2510.13565v2 Announce Type: replace Abstract: Depth estimation remains central to autonomous driving, and radar-camera fusion offers robustness in adverse conditions by providing complementary g

activegraph longmemeval experiment #1: https://x.com/ActiveGraphAI/status/2059106393433780292?s=20 [technical blog post] “Evidence Compilation Before Semantic Memory: ActiveGraph on LongMemEval-S” ——

In this post, we walk through a practical implementation using KDB-X MCP server integration with Amazon Quick, demonstrating how traders and analysts can ask questions using conversational language an

arXiv:2605.30569v1 Announce Type: new Abstract: Robotic manipulation dexterity is often pursued by building increasingly complex high-DoF multifingered hands. While many robotic hands are designed to

arXiv:2605.31256v1 Announce Type: new Abstract: Embodied Large Language Models (LLMs) are increasingly used as reasoning modules in robotic control pipelines to improve human-robot interaction, but th

Harrison Chase compares LangSmith Engine to Tesla's 'Full Self-Driving' moment, suggesting it represents a significant advancement in AI engineering capabilities and automation. The post indicates Lan

arXiv:2605.30983v1 Announce Type: new Abstract: Despite the remarkable success of multi-modal bird's-eye view (BEV) perception in autonomous driving, current systems exhibit a critical vulnerability:

arXiv:2605.31251v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown strong potential as embodied agents, yet embodied geo-localization remains underexplored due to th

While deploying Model Context Protocol (MCP) servers in production, enterprises need fine-grained access control across servers, observability into which teams use which tools, security guarantees aga

arXiv:2605.30884v1 Announce Type: new Abstract: Existing agentic reinforcement learning methods for GUI grounding have limitations at two levels. At the data level, current approaches typically treat