Search: “agents”

arXiv:2604.19270v1 Announce Type: new Abstract: As groups of robots increasingly collaborate with humans, understanding how humans perceive them is critical for designing effective human-robot teams.

arXiv:2604.16408v1 Announce Type: new Abstract: We present Speaking Memories, a distributed, stakeholder-in-the-loop robotic interaction platform for personalized cognitive exercise support. Rather th

arXiv:2604.16349v1 Announce Type: cross Abstract: Retrieving real-time information is a fundamental capability for search-integrated agents in real-world applications. However, existing benchmarks are

arXiv:2604.17244v1 Announce Type: new Abstract: Despite the rapid progress, LLMs for sequential decision-making (i.e., LLM agents) still struggle to produce diverse outputs. This leads to insufficient

arXiv:2604.16868v1 Announce Type: new Abstract: State estimation is a fundamental requirement in robotics, where the accurate determination of a robot's state is essential for stable operation despite

arXiv:2604.17944v1 Announce Type: new Abstract: Developing agents capable of navigating fragmented, multi-source information remains challenging, primarily due to the scarcity of benchmarks reflecting

arXiv:2604.16585v1 Announce Type: new Abstract: We present the Global Neural World Model (GNWM), a self-stabilizing framework that achieves topological quantization through balanced continuous entropy

arXiv:2604.16086v1 Announce Type: cross Abstract: One of the dominant paradigms in self-supervised learning (SSL), illustrated by MoCo or DINO, aims to produce robust representations by capturing feat

arXiv:2512.08230v2 Announce Type: replace Abstract: Learning about the causal structure of the world is a fundamental problem for human cognition. Causal models and especially causal learning have pro

arXiv:2604.13890v1 Announce Type: cross Abstract: Why do capitalist economies recurrently generate crises whose severity is disproportionate to the size of the triggering shock? This paper proposes a

arXiv:2604.13822v1 Announce Type: new Abstract: MLLM-based GUI agents have demonstrated strong capabilities in complex user interface interaction tasks. However, long-horizon scenarios remain challeng

arXiv:2604.11950v1 Announce Type: cross Abstract: While recent LLM-based agents can identify many candidate bugs in source code, their reports remain static hypotheses that require manual validation,

arXiv:2604.12857v1 Announce Type: new Abstract: Autonomous vehicles (AVs) are now operating on public roads, which makes their testing and validation more critical than ever. Simulation offers a safe

arXiv:2604.12933v1 Announce Type: cross Abstract: Marine ecosystem degradation necessitates continuous, scientifically selective underwater monitoring. However, most autonomous underwater vehicles (AU

arXiv:2511.17714v5 Announce Type: replace Abstract: Standard decision frameworks address uncertainty about facts but assume fixed options and values. We extend the Jeffrey-Bolker framework to model re

arXiv:2604.12955v1 Announce Type: new Abstract: There is growing interest in leveraging large language models (LLMs) for text-to-model translation and optimization tasks. This paper aims to advance th

arXiv:2604.12766v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) typically relies on a flat retrieval paradigm that maps queries directly to static, isolated text segments. This ap

arXiv:2604.12086v1 Announce Type: new Abstract: Designing robust reinforcement learning (RL) agents in the presence of imperfect reward signals remains a core challenge. In practice, agents are often

arXiv:2604.09564v1 Announce Type: cross Abstract: We present ACE-Bench (Azure SDK Coding Evaluation Benchmark), an execution-free benchmark that provides fast, reproducible pass or fail signals for wh

arXiv:2604.05663v2 Announce Type: replace Abstract: Traffic signal control (TSC) is a core component of intelligent transportation systems (ITS), aiming to reduce congestion, emissions, and travel tim

arXiv:2603.09172v4 Announce Type: replace-cross Abstract: We present improved lower bounds for seven classical Ramsey numbers: mathbf{R}(3, 13) is increased from 60 to 61, mathbf{R}(3, 18) from 99 to

arXiv:2604.07512v2 Announce Type: replace Abstract: We present Rhizome OS-1, a semi-autonomous operating system for small molecule drug discovery in which multi-modal AI agents operate as a full multi

arXiv:2604.11466v1 Announce Type: cross Abstract: Large Language Model (LLM) agents offer a potentially-transformative path forward for generative social science but face a critical crisis of validity

arXiv:2603.23315v3 Announce Type: replace-cross Abstract: When providers update AI companions, users report grief, betrayal, and loss. A growing literature asks whether the norms governing personal re

arXiv:2604.09304v1 Announce Type: new Abstract: For decades, Physically-Based Rendering (PBR) is the fundation of synthesizing photorealisitic images, and therefore sometimes roughly referred as Photo

arXiv:2604.08594v1 Announce Type: cross Abstract: The widespread adoption of generative artificial intelligence conversational agents (AICAs) among university students constitutes a novel cognitive so

arXiv:2604.08712v1 Announce Type: new Abstract: The generation of planning domains from natural language descriptions remains an open problem even with the advent of large language models and reasonin

arXiv:2604.09009v1 Announce Type: new Abstract: Adaptive medical AI models often face performance drops in dynamic clinical environments due to data drift. We propose an autonomous continuous monitori

arXiv:2604.09115v1 Announce Type: cross Abstract: Wilderness Search and Rescue (WiSAR) represents a longstanding and critical societal challenge, demanding innovative and automatic technological solut

arXiv:2604.06531v2 Announce Type: cross Abstract: The mean-field Schrodinger bridge (MFSB) problem concerns designing a minimum-effort controller that guides a diffusion process with nonlocal intera

arXiv:2604.06742v1 Announce Type: cross Abstract: Large Language Models (LLMs) are driving a shift towards intent-driven development, where agents build complete software from scratch. However, existi

arXiv:2512.19576v5 Announce Type: replace-cross Abstract: Attitude control is essential for many satellite missions. Classical controllers, however, are time-consuming to design and sensitive to model

arXiv:2604.07774v1 Announce Type: cross Abstract: This paper focuses on embodied task planning, where an agent acquires visual observations from the environment and executes atomic actions to accompli

arXiv:2604.07415v1 Announce Type: cross Abstract: Large language models (LLMs) are probabilistic in nature and perform more reliably when augmented with external information. As complex queries often

arXiv:2608.12753v1 Announce Type: new Abstract: We study decentralized multi-player reinforcement learning in episodic tabular Markov decision processes (MDPs) under three forms of information asymmet

arXiv:2608.13096v1 Announce Type: new Abstract: Limit order book (LOB) simulators are most useful to practitioners when they combine realistic market dynamics, computationally efficient sampling, cont

arXiv:2608.13448v1 Announce Type: new Abstract: Social robots are expected to operate across diverse environments, where similar arrangements can imply different socially appropriate actions, e.g., st

arXiv:2512.19799v2 Announce Type: replace Abstract: Advances in LLM reasoning and tool use have enabled agentic science, yet frontier theoretical and computational physics remains challenging because

arXiv:2608.11247v1 Announce Type: new Abstract: Recent advances in language models have enabled collaborative settings in which multiple models leverage one another's capabilities, iteratively improvi

arXiv:2608.11876v1 Announce Type: new Abstract: Training and validation of Embodied AI for social navigation critically depends on realistic simulation environments, yet many current approaches fail t

arXiv:2608.11901v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) has progressively expanded from indoor to outdoor environments. However, existing outdoor VLN datasets still rely o

arXiv:2608.11220v1 Announce Type: new Abstract: Nowadays, the creation of a process flow diagram (PFD) and its subsequent transformation into a piping and instrumentation diagram (P&ID) is predominant

arXiv:2608.11340v1 Announce Type: cross Abstract: Symbolic network verifiers can reason about correctness across vast spaces of routing inputs and failures, but only for the protocols and features an

arXiv:2608.11676v1 Announce Type: new Abstract: Heterogeneous multi-agent LLM systems, where agents are powered by different model families, can outperform homogeneous configurations by reducing redun

arXiv:2509.05624v3 Announce Type: replace-cross Abstract: How much information about an agent's underlying values can be recovered from its observable behavior? This question matters for any approach

arXiv:2608.10438v1 Announce Type: new Abstract: Large language models increasingly rely on external tools to access up-to-date information, perform computation, and interact with the outside world. Fo