Search: “framework”

arXiv:2606.04345v1 Announce Type: cross Abstract: This paper presents HYolo, an intelligent IoT-based object detection framework that integrates hypergraph learning into the YOLO architecture. Traditi

arXiv:2606.04227v1 Announce Type: cross Abstract: We present an algorithmic framework for incremental maintenance of first sheaf cohomology H^1(X; F) on dynamically evolving 1-dimensional cellular com

arXiv:2606.04404v1 Announce Type: cross Abstract: The deep neural network is a widely used framework in machine learning that has been widely applied in various fields. However, deep neural networks o

arXiv:2606.04392v1 Announce Type: cross Abstract: This study develops a two-domain physics-informed neural network framework for contaminant transport through a GCL/SL composite liner system, in which

arXiv:2602.23214v2 Announce Type: replace Abstract: Plug-and-Play diffusion prior (PnPDP) frameworks have emerged as a powerful paradigm for solving imaging inverse problems by treating pretrained gen

arXiv:2606.04104v1 Announce Type: cross Abstract: Agent systems execute through runtimes with very different control points: local coding tools, framework SDKs, managed agent platforms, API gateways,

arXiv:2603.02697v2 Announce Type: replace-cross Abstract: This paper presents ShareVerse, a video generation framework enabling multi-agent shared world modeling, addressing the gap in existing works

arXiv:2606.04505v1 Announce Type: new Abstract: Scientific simulators are increasingly being integrated into LLM-driven systems for high-stakes simulation-driven decision-making. However, existing fra

arXiv:2606.04455v1 Announce Type: new Abstract: Current AI benchmarks evaluate agents on task execution within human-designed workflows. These evaluations fundamentally fail to measure a critical next

arXiv:2606.04355v1 Announce Type: new Abstract: Partially Observable Markov Decision Processes (POMDPs) are a general and principled framework for motion planning under uncertainty. Despite tremendous

arXiv:2606.05029v1 Announce Type: cross Abstract: Controlled experiments are the backbone of machine learning research, but at the scale of modern foundation models, they have become prohibitively exp

This OpenAI publication outlines a proposed framework for establishing democratic oversight and governance structures for advanced AI systems, addressing how frontier AI development should be regulate

arXiv:2606.03972v1 Announce Type: new Abstract: We present AAD-1, an Asymmetric Adversarial Distillation framework for One-step autoregressive image-to-video generation. State-of-the-art methods adopt

arXiv:2606.02604v1 Announce Type: cross Abstract: ESG and climate risk data remain fragmented across heterogeneous Scope 1, Scope 2, and Scope 3 reporting environments, while conventional validation p

B9493 is a release of llama.cpp, an LLM inference framework in C/C++ . This release includes updates to model support, such as centralized hidden activation mappings and additions for granite embeddin

arXiv:2602.12221v2 Announce Type: replace Abstract: We propose UniDFlow, a unified discrete flow-matching framework for multimodal understanding, generation, and editing. It decouples understanding an

arXiv:2606.03061v1 Announce Type: cross Abstract: Emerging distributed computing paradigms, such as the computing continuum, are inherently heterogeneous, stochastic, and complex. Efficiently and effe

arXiv:2606.03628v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable progress in open-ended text generation, yet they remain prone to hallucinating incorrect or unsu

arXiv:2602.01483v2 Announce Type: replace-cross Abstract: We propose causal preference elicitation, a Bayesian framework for expert-in-the-loop causal discovery that actively queries local edge relati

arXiv:2507.19684v2 Announce Type: replace-cross Abstract: Socially interactive humanoid robots must engage with humans through their bodies, adapting in real time to a partner's movement, intent, and

arXiv:2606.02982v1 Announce Type: cross Abstract: The rapid growth of large language model (LLM) inference services has increased the demand for efficient multi-tenant GPU scheduling. While modern inf

arXiv:2606.02634v1 Announce Type: cross Abstract: We introduce Echo-POSED, a self-supervised framework for real-time transthoracic echocardiography (TTE) guidance that recommends probe adjustments dir

arXiv:2606.02602v1 Announce Type: cross Abstract: In computational pathology, Whole Slide Images (WSIs) survival analysis is crucial for patient prognosis assessment, but it faces multiple technical c

arXiv:2510.16282v2 Announce Type: replace Abstract: Personalized large language models (LLMs) tailor content to individual preferences using user profiles or histories. However, existing parameter-eff

The `create_agent` function in LangChain provides a minimal, lightweight agent framework designed for easy customization through middleware, enabling developers to build task-specific agent harnesses

arXiv:2505.23725v3 Announce Type: replace Abstract: DiLoCo is a powerful framework for training large language models (LLMs), enabling larger optimal batch sizes and increased accelerator utilization

arXiv:2606.03915v1 Announce Type: new Abstract: We propose PatchScene, a novel diffusion-based framework for large-scale LiDAR scene completion. Unlike existing methods that rely on global latent repr

Qiskit Fall Fest 2026 is an event organized by IBM that focuses on quantum computing education and community engagement through the open-source Qiskit framework. The event likely provides opportunitie

arXiv:2606.03969v1 Announce Type: cross Abstract: Reliable uncertainty communication is critical to the trustworthiness of LLMs, yet faithful calibration (FC)--the alignment between models' intrinsic

arXiv:2606.03080v1 Announce Type: cross Abstract: Causal language models factorize sequence probabilities using only preceding context, leaving future information unexploited during training despite i

arXiv:2606.03019v1 Announce Type: cross Abstract: Copyleft, as implemented in licenses such as the GNU General Public License, was a legal hack that used copyright to guarantee user freedom by tying t

arXiv:2606.03963v1 Announce Type: cross Abstract: Deep reinforcement learning has shown strong potential for enabling autonomous robots to learn complex navigational tasks. However, its practical use

arXiv:2606.02664v1 Announce Type: cross Abstract: Latent state-space models are widely used to study partially observed dynamical systems, yet most formulations assume that process variability is inde

arXiv:2606.03689v1 Announce Type: cross Abstract: Survival Analysis (SA) is a statistical framework that models the time span until some event of interest occurs. Widely used in several domains, inclu

arXiv:2601.23229v2 Announce Type: replace Abstract: Markov decision processes (MDPs) are a fundamental model in sequential decision making. Robust MDPs (RMDPs) extend this framework by allowing uncert

arXiv:2511.17126v4 Announce Type: replace-cross Abstract: Emerging deep-learning-based lens library pre-training (LensLib-PT) pipeline offers a new avenue for blind lens aberration correction by train

Trump signed an executive order on June 2, 2026, establishing a voluntary framework for the federal government to evaluate risks posed by advanced AI systems before release and encouraging companies t

arXiv:2606.01933v1 Announce Type: new Abstract: This paper presents our winning methodology for the CASTLE 2026 Challenge at the CVPR 2026 EgoVis Workshop, where our team secured third place globally.

arXiv:2606.00320v1 Announce Type: new Abstract: We present an online, distribution-free framework for controlling the Conditional Value-at-Risk (CVaR), extending conformal tail risk control to non-sta

This Databricks resource presents a framework for assessing and advancing an organization's AI governance capabilities through a maturity model structure. It likely provides a matrix for evaluating cu

NVIDIA announced three new offerings: Cosmos 3, an advanced video generation model; Nemotron 3 Ultra, an upgraded language model; and RTX Spark, likely a tool or framework for developers. These releas

arXiv:2606.01362v1 Announce Type: cross Abstract: Video generative models have achieved remarkable progress in synthesizing photorealistic video sequences. However, enabling broader and more creative

arXiv:2606.00640v1 Announce Type: new Abstract: A new framework for the estimation of the complexity posed by video-question pairs to video-LLMs, Video Attribute-Based Complexity (VideoABC), is propos

arXiv:2606.00461v1 Announce Type: new Abstract: Tremor is a common movement disorder associated with conditions like Parkinson's disease and Essential tremor, traditionally diagnosed through expert cl

arXiv:2606.02045v1 Announce Type: cross Abstract: Artificial intelligence provides a practical framework for crop damage assessment from imagery data, supporting early decision-making in agricultural

arXiv:2604.03789v2 Announce Type: replace-cross Abstract: Recent advances in large language models have significantly improved their ability to perform mathematical reasoning, extending from elementar