Search: “framework”

arXiv:2605.26307v1 Announce Type: cross Abstract: Software-Defined Networking (SDN) provides flexible and programmable network management; however, its centralized control architecture remains highly

arXiv:2605.24950v1 Announce Type: cross Abstract: We present ARCANE-PedSynth, an open-source CARLA-based software framework for generating synthetic multi-pedestrian datasets with dense behavioural an

arXiv:2605.18776v1 Announce Type: cross Abstract: The rapid spread of misinformation on social media highlights the need for robust, automated fact correction frameworks. However, existing works rely

arXiv:2605.17232v1 Announce Type: new Abstract: Discrete diffusion has become a leading framework for generative modeling in various applications including language, vision, and biology. Existing conv

arXiv:2605.12654v1 Announce Type: new Abstract: Replicating and surpassing the autonomy of natural organisms remains a long-standing goal in robotics. Yet most robotic systems have their structure, ma

arXiv:2605.09186v1 Announce Type: new Abstract: Mixed-integer programming (MIP) research is both mathematically sophisticated and engineering-intensive: testing an algorithmic hypothesis within a bran

arXiv:2605.09659v1 Announce Type: new Abstract: Koopman operator theory provides a powerful framework for representing nonlinear dynamics through a linear operator acting on lifted observables, enabli

arXiv:2605.09045v1 Announce Type: new Abstract: Agentic frameworks are the software layer through which AI agents act in the world. Existing safety methods intervene on the model and therefore remain

arXiv:2603.26114v2 Announce Type: replace Abstract: DPD-Cancer is a graph-attention deep learning framework for predicting small-molecule DPD-Cancer is a graph-attention deep learning framework for pr

arXiv:2605.04997v1 Announce Type: new Abstract: DualTCN is the first deep-learning framework for inverting time-domain marine controlled-source electromagnetic (MCSEM) transient data. Moving away from

AI coding agents are rapidly becoming ubiquitous across the software industry, fundamentally changing how developers write, test, and debug daily code. While these tools excel at localized, self-conta

arXiv:2605.02050v1 Announce Type: cross Abstract: This work establishes a foundational framework for standardizing AI evaluation RCTs (sometimes called human uplift studies). Drawing on established ex

In this post, we introduce a systematic framework for LLM migration or upgrade in generative AI production, encompassing essential tools, methodologies, and best practices. The framework facilitates t

arXiv:2604.26910v1 Announce Type: new Abstract: This paper presents a planning pipeline framework for locomotion in rope-assisted robots climbing vertical surfaces. The proposed framework is formulate

arXiv:2602.11224v3 Announce Type: replace-cross Abstract: We present Agent-Diff, a novel benchmarking framework for evaluating agentic Large Language Models (LLMs) on real-world productivity software

arXiv:2512.21372v2 Announce Type: replace-cross Abstract: The accurate classification of gastrointestinal diseases from endoscopic and histopathological imagery remains a significant challenge in medi

arXiv:2604.23483v1 Announce Type: new Abstract: Multi-component natural language processing (NLP) pipelines are increasingly deployed for high-stakes decisions, yet no existing adversarial method can

arXiv:2604.23003v1 Announce Type: new Abstract: In this paper, we propose a Physics-Informed Neural Network framework for time-dependent simulations of pollution propagation originating from moving em

arXiv:2509.00081v2 Announce Type: replace-cross Abstract: Effective Cyber Threat Intelligence (CTI) relies upon accurately structured and semantically enriched information extracted from cybersecurity

arXiv:2604.22857v1 Announce Type: new Abstract: This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional ne

arXiv:2509.20086v2 Announce Type: replace Abstract: Phonemization is a critical component in text-to-speech synthesis. Traditional approaches rely on deterministic transformations and lexica, while ne

arXiv:2604.23575v1 Announce Type: cross Abstract: Silicon samples are increasingly used as a low-cost substitute for human panels and have been shown to reproduce aggregate human opinion with high fid

arXiv:2604.23674v1 Announce Type: new Abstract: With the emergence of large language models (LLMs) and AI agent frameworks, the human-AI co-work paradigm known as Vibe Coding is changing how people co

arXiv:2604.22189v1 Announce Type: new Abstract: This letter presents an energy-efficient multi-robot coverage path planning (MRCPP) framework for large, nonconvex Regions of Interest (ROI) containing

arXiv:2604.21740v1 Announce Type: cross Abstract: Discrete-event systems and supervisory control theory provide a rigorous framework for specifying correct-by-construction behavior. However, their pra

arXiv:2604.21849v1 Announce Type: cross Abstract: Bayesian Optimal Experimental Design (BOED) provides a rigorous framework for decision-making tasks in which data acquisition is often the critical bo

arXiv:2604.21444v1 Announce Type: new Abstract: Long-form video understanding remains fundamentally challenged by pervasive spatiotemporal redundancy and intricate narrative dependencies that span ext

arXiv:2604.21617v1 Announce Type: new Abstract: Parametric projections let analysts embed new points in real time, but input variations from measurement noise or data drift can produce unpredictable s

arXiv:2604.21003v1 Announce Type: new Abstract: AI agents are increasingly deployed on complex, domain-specific workflows -- navigating enterprise web applications that require dozens of clicks and fo

arXiv:2506.15518v2 Announce Type: replace Abstract: This paper presents a framework for the real-time initialization of unknown Ultra-Wideband (UWB) anchors in UWB-aided navigation systems. The method

arXiv:2604.20601v1 Announce Type: new Abstract: We introduce SuperIgor, a framework for instruction-following tasks. Unlike prior methods that rely on predefined subtasks, SuperIgor enables a language

arXiv:2604.19825v1 Announce Type: cross Abstract: State-of-the-art code generation frameworks rely on mental simulation, where LLMs internally trace execution to verify correctness. We expose a fundam

arXiv:2507.09861v2 Announce Type: replace-cross Abstract: Visually Rich Document Understanding (VRDU) has become a pivotal area of research, driven by the need to automatically interpret documents tha

arXiv:2602.12708v2 Announce Type: replace Abstract: Vertical Federated Learning (VFL) has emerged as a critical paradigm for collaborative model training in privacy-sensitive domains such as finance a

arXiv:2604.00555v2 Announce Type: replace Abstract: Enterprise adoption of Large Language Models (LLMs) is constrained by hallucination, domain drift, and the inability to enforce regulatory complianc

arXiv:2509.05890v3 Announce Type: replace-cross Abstract: Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to t

arXiv:2509.03070v4 Announce Type: replace-cross Abstract: This letter presents a CWT-enhanced vibration sensing framework for bearing fault monitoring through spatial localization on time-frequency sp

arXiv:2604.17106v1 Announce Type: new Abstract: Motivated by the challenge presented by non-Markovian objectives in reinforcement learning (RL), we present a novel framework to track and represent the

arXiv:2604.18548v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a powerful framework for learning governing equations of dynamical systems from data. Biologically-info

arXiv:2604.17212v1 Announce Type: new Abstract: This paper presents a framework for safe navigation of a unicycle point robot to a goal position in an environment populated with obstacles from almost

arXiv:2307.08336v2 Announce Type: replace Abstract: Despite the numerous applications of convex constraints in Robotics, enforcing them within learning-based frameworks remains an open challenge. Exis

ReasoningBank is a memory framework that distills generalizable reasoning strategies from an agent's successful and failed experiences, which the agent retrieves at test time to inform interactions wh

arXiv:2604.17381v1 Announce Type: cross Abstract: This paper proposes StrEBM, a structured latent energy-based model for source-wise structured representation learning. The framework is motivated by a

arXiv:2507.14922v2 Announce Type: replace Abstract: Persona-driven simulations are increasingly used in computational social science, yet their validity critically depends on the fidelity of the under

arXiv:2602.14757v2 Announce Type: replace-cross Abstract: We develop an interpolation-based modeling framework for parameter-dependent partial differential equations arising in control, inverse proble

arXiv:2604.15972v1 Announce Type: new Abstract: LLM-driven multi-agent frameworks address complex reasoning tasks through multi-role collaboration. However, existing approaches often suffer from reaso