Search: “framework”

Qwen3.6 27B is a 27-billion parameter language model that can achieve approximately 60 tokens per second throughput when running on dual RTX 5060 Ti GPUs with 16GB memory each, using the vLLM inferenc

arXiv:2604.25325v1 Announce Type: cross Abstract: Modern Text-to-SQL systems generate multiple candidate SQL queries and rank them to judge a final prediction. However, existing methods face two limit

arXiv:2604.25310v1 Announce Type: new Abstract: This work addresses the critical problem of tracking fast-moving objects through strongly scattering media in a low-light environment. Different from ex

arXiv:2604.25698v1 Announce Type: new Abstract: Tendon-Driven Continuum Robots (TDCRs) pose significant control challenges due to their highly nonlinear, path-dependent dynamics and non-Markovian char

arXiv:2502.15792v2 Announce Type: replace-cross Abstract: Autonomous vehicles (AVs) make driving decisions without humans, making dependability assurance critical. Scenario-based testing is widely use

arXiv:2511.03473v2 Announce Type: replace Abstract: In many real-world reinforcement learning (RL) problems, the environment exhibits inherent symmetries that can be exploited to improve learning effi

arXiv:2506.05205v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to solve complex tasks where they must retrieve and compose many pieces of in-context information

arXiv:2604.25128v1 Announce Type: new Abstract: Recent advances in diffusion models have enabled high-quality image generation, leading to increasing demand for post-generation editing that modifies l

arXiv:2510.10150v3 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) serves as a cornerstone technique for enhancing the reasoning capabilities of Large Language M

arXiv:2602.11075v2 Announce Type: replace Abstract: Despite the sustained scaling on model capacity and data acquisition, Vision-Language-Action (VLA) models remain brittle in contact-rich and dynamic

arXiv:2604.25889v1 Announce Type: new Abstract: Current deepfake detection models achieve state-of-the-art performance on pristine academic datasets but suffer severe spatial attention drift under rea

arXiv:2604.25404v1 Announce Type: new Abstract: Graph-based representations such as Scene Graphs enable localization in structured indoor environments by matching a locally observed graph, constructed

arXiv:2603.17729v3 Announce Type: replace Abstract: Recent advances in Large Vision-Language Models (LVLMs) have enabled training-free Fine-Grained Visual Recognition (FGVR). However, effectively expl

Scary that he doesn’t know this. Elon Musk just said on the witness stand that he doesn't know what a 'safety card' is with regard to AI development... 'Why would it be a card?' He also says he doesn'

arXiv:2604.25292v1 Announce Type: new Abstract: This paper addresses the problem of traffic congestion management in fixed-wing unmanned aerial vehicle (UAV) corridors by further developing a recently

arXiv:2602.10718v3 Announce Type: replace-cross Abstract: While FP8 attention has shown substantial promise in innovations like FlashAttention-3, its integration into the decoding phase of the DeepSee

arXiv:2602.22243v2 Announce Type: replace Abstract: The online fusion and tracking of static objects from heterogeneous sensor detections is a fundamental problem in robotics, autonomous systems, and

arXiv:2604.25272v1 Announce Type: cross Abstract: Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this work, we study a bandit problem where the payoffs

arXiv:2604.24934v1 Announce Type: new Abstract: Intelligent Transportation Systems (ITS) increasingly rely on vision-based perception and learning-based control, necessitating experimental platforms t

arXiv:2603.19124v2 Announce Type: replace Abstract: This paper presents the design, modeling, and fabrication of 3D-printed, tendon-actuated continuum robots featuring a flexible, tapered backbone con

The momentum is undeniable: the world’s fastest-growing AI startups are building with Google Cloud. Instead of stitching together fragmented point solutions, founders are building their businesses her

arXiv:2604.00485v2 Announce Type: replace Abstract: Dimension reduction (DR) is inherently non-unique: multiple embeddings can preserve the structure of high-dimensional data equally well while differ

arXiv:2604.25150v1 Announce Type: new Abstract: Overparameterization is central to the success of deep learning, yet the mechanisms by which it improves optimization remain incompletely understood. We

arXiv:2604.25299v1 Announce Type: new Abstract: Diffusion models have achieved success in high-fidelity data synthesis, yet their capacity for more complex, structured reasoning like text following ta

arXiv:2604.25545v1 Announce Type: new Abstract: Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical i

arXiv:2604.25131v1 Announce Type: new Abstract: Recent self-supervised pre-training methods for electroencephalogram (EEG) have shown promising results. However, the pre-trained models typically requi

At UKG, we’ve spent years building and expanding our human capital management (HCM) and workforce management (WFM) solutions with new products, capabilities, and a series of acquisitions. Our cloud pl

arXiv:2511.07743v3 Announce Type: replace Abstract: Ultrasound imaging is a cornerstone of non-invasive clinical diagnostics, yet its limited field of view poses challenges for novel view synthesis. W

arXiv:2511.14183v3 Announce Type: replace Abstract: Digital images are often degraded by soft effects such as lens flare, haze, shadows, and reflections, which reduce aesthetics even though the underl

arXiv:2410.09635v2 Announce Type: replace Abstract: Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, acc

arXiv:2409.11063v3 Announce Type: replace-cross Abstract: Variational principles play a central role in classical mechanics, providing compact formulations of dynamics and direct access to conserved q

arXiv:2604.25235v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used as automated judges for multimodal systems, yet their scores provide no indication of reliability.

arXiv:2604.25132v1 Announce Type: new Abstract: Instruction-tuning datasets often contain substantial redundancy and low-quality samples, necessitating effective data selection methods. We propose an

arXiv:2510.07499v2 Announce Type: replace Abstract: Recent Long-Context Language Models (LCLMs) can process hundreds of thousands of tokens in a single prompt, enabling new opportunities for knowledge

arXiv:2603.14248v2 Announce Type: replace-cross Abstract: Large language model (LLM) web agents are increasingly used for web navigation but remain far from human reliability on realistic, long-horizo

arXiv:2604.25011v1 Announce Type: new Abstract: Reinforcement learning (RL)-based post-training often improves the reasoning performance of large language models (LLMs) beyond the training domain, whi

arXiv:2604.25012v1 Announce Type: new Abstract: Automated agentic workflow design currently relies on per-task iterative search, which is computationally prohibitive and fails to reuse structural know

arXiv:2604.23935v1 Announce Type: new Abstract: Audio-based video object segmentation aims to locate and segment objects in videos conditioned on audio cues, requiring precise understanding of both ap

arXiv:2604.24149v1 Announce Type: new Abstract: Remote sensing images are frequently degraded by adverse weather conditions, particularly clouds and haze, which severely impair downstream applications

arXiv:2604.23790v1 Announce Type: new Abstract: A central problem in unsupervised domain adaptation is determining what to transfer from labeled source domains to an unlabeled target domain. To handle

arXiv:2604.24037v1 Announce Type: new Abstract: Emergent intelligence have played a major role in the modern AI development. While existing studies primarily rely on empirical observations to characte

arXiv:2507.22345v2 Announce Type: replace Abstract: Wheel-legged robots integrate leg agility on rough terrain with wheel efficiency on flat ground. However, most existing designs do not fully capital

arXiv:2604.23821v1 Announce Type: cross Abstract: Autonomous neutron spectroscopy must solve three distinct tasks: detection (where is the signal?), inference (which Hamiltonian governs it?), and refi

arXiv:2508.10599v4 Announce Type: replace Abstract: Activation steering offers a promising approach to controlling the behavior of Large Language Models by directly manipulating their internal activat

arXiv:2407.05595v3 Announce Type: replace Abstract: Medical palpation is more than force transmission. It is a bidirectional cognitive and emotional exchange between doctor and patient. We model two c

arXiv:2510.15479v2 Announce Type: replace Abstract: We study counterfactual prediction under assignment bias and propose a mathematically grounded, information-theoretic approach that removes treatmen