Knowledge catalogue
arXiv:2510.24411v3 Announce Type: replace Abstract: Computer-using agents powered by Vision-Language Models (VLMs) have demonstrated human-like capabilities in operating digital environments like mobi
arXiv:2607.23194v1 Announce Type: new Abstract: Scene Text Recognition (STR) models are trained almost exclusively on word crops of at most 25 characters, yet real deployments (signage, product labels
arXiv:2607.23731v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own trajectories while a teacher supplies dense token-level likelihoods at student-visited prefixes
arXiv:2607.23772v1 Announce Type: cross Abstract: We study a restless multi-armed bandit (RMAB) problem for a stochastic deadline scheduling application. RMAB problems are solved using the Whittle ind
arXiv:2607.24296v1 Announce Type: new Abstract: Diffusion Policies (DPs) are able to perform complex manipulation tasks. However, DPs are typically trained by minimizing a denoising objective, which p
arXiv:2607.24703v1 Announce Type: new Abstract: Female pelvic diseases remain an under researched area characterized by often delayed diagnosis. While pelvic MRI offers superior soft-tissue contrast f
arXiv:2607.22695v1 Announce Type: new Abstract: Large Language Models (LLMs) are capable of generalizing human language for the completion of never-before-seen tasks, leading to widespread deployment.
arXiv:2602.05387v2 Announce Type: replace Abstract: MRI provides superior soft tissue contrast without ionizing radiation; however, the absence of electron density information limits its direct use fo
arXiv:2510.06128v2 Announce Type: replace Abstract: Tokenization forms the basis of multilingual language models, yet existing methods often limit cross-lingual transfer by mapping semantically equiva
arXiv:2607.23694v1 Announce Type: new Abstract: Efficient surgical segmentation empowers clinical diagnosis, intraoperative monitoring, and downstream robotic pipelines for reconstruction and simulati
arXiv:2607.23225v1 Announce Type: new Abstract: As chip manufacturing processes advance to deep submicron nodes, parasitic interconnect effects increasingly dominate the performance of analog and mixe
arXiv:2607.22588v1 Announce Type: new Abstract: Modern compute-intensive software must migrate across a changing ecosystem of accelerators, programming APIs, compiler stacks, and portability layers, i
arXiv:2607.23293v1 Announce Type: cross Abstract: Image-source-method (ISM)-based room impulse response (RIR) simulation is a useful and physically interpretable tool for acoustic scene modeling, but
arXiv:2607.23794v1 Announce Type: cross Abstract: Pathological diagnosis is inherently multi-scale, requiring the integration of global tissue architecture at low magnification with cellular morpholog
arXiv:2607.23631v1 Announce Type: new Abstract: Gigapixel Whole-Slide Images (WSIs) present a fundamental computational bottleneck for vision-language models (VLMs) due to extreme sequence lengths. Ex
arXiv:2607.23343v1 Announce Type: cross Abstract: Intraoperative 2D/3D registration aligns preoperative CT volumes with intraoperative X-ray or fluoroscopic images and is essential for image-guided in
arXiv:2607.22859v1 Announce Type: new Abstract: Mathematical Word Problems (MWPs) are an important benchmark for evaluating natural language understanding and quantitative reasoning. Despite recent pr
arXiv:2607.22726v1 Announce Type: new Abstract: Despite advances in Video Large Language Models (VLLMs) that have displayed promising outcomes in video understanding, the redundancy in the long-durati
arXiv:2505.17492v2 Announce Type: replace Abstract: Project duplication detection is critical for project quality assessment because it helps avoid investment in repeated proposals. Existing methods u
arXiv:2603.27476v2 Announce Type: replace Abstract: AI-powered people search platforms are increasingly used in recruiting, sales prospecting, and professional networking, yet no widely accepted bench
arXiv:2607.23680v1 Announce Type: new Abstract: Semantic segmentation in agricultural imagery is often evaluated under in-domain protocols, yet practical deployment requires robustness to appearance p
arXiv:2607.24345v1 Announce Type: new Abstract: Neural spectral PDE solvers often learn an entire unresolved vector field even when an inexpensive approximate model can already capture most of the tra
arXiv:2607.23447v1 Announce Type: new Abstract: Predicting cellular responses to unseen chemical perturbations is challenging due to unknown targets and mechanisms, high-dimensional expression respons
arXiv:2411.00967v2 Announce Type: replace Abstract: The future of agriculture is intertwined with automation. Accurate fruit detection, yield estimation, and harvest time prediction are crucial for ef
arXiv:2607.22573v1 Announce Type: new Abstract: Imaginary phonon modes remain a practical bottleneck in computational materials screening because otherwise plausible structures can be locally dynamica
arXiv:2607.23285v1 Announce Type: cross Abstract: Photonic reservoir computing has attracted increasing attention as a fast and low-cost approach for time-series prediction. Photonic reservoir computi
arXiv:2607.22877v1 Announce Type: new Abstract: With the emergence of Physical AI, artificial intelligence is extending beyond screen-based applications to embodied systems that perceive, interact wit
arXiv:2607.22797v1 Announce Type: cross Abstract: Trustworthy deployment of AI-based diagnosis in safety-critical mechanical systems hinges on validation: whether a prediction can be checked against p
arXiv:2607.24274v1 Announce Type: cross Abstract: Inverse design of three-dimensional porous media is central to applications in filtration, catalysis, energy storage, fuel cells, thermal management,
arXiv:2607.23501v1 Announce Type: new Abstract: Locating periodic solutions of chaotic dynamical systems normally requires an initial guess close enough to the target orbit for numerical continuation
arXiv:2607.23880v1 Announce Type: cross Abstract: Nitrous oxide (N_2O) is the dominant ozone-depleting substance emitted in the 21st century, and the third largest contributor to anthropogenic greenho
arXiv:2607.24513v1 Announce Type: new Abstract: Transformer architectures have attracted increasing attention for solving partial differential equations (PDEs), owing to their flexibility in handling
arXiv:2607.24593v1 Announce Type: new Abstract: Token-level sparse attention, as implemented by DeepSeek Sparse Attention (DSA) in production systems, makes the downstream attention efficient but shif
arXiv:2607.23491v1 Announce Type: cross Abstract: Two structural insights have been overlooked in automated residential floor plan generation. First, design is inherently progressive. Architects begin
arXiv:2607.23670v1 Announce Type: cross Abstract: Plan Modes have become standard features in agentic programming tools, allowing users to gain transparency and control by working with the agent to de
arXiv:2607.23975v1 Announce Type: new Abstract: Large language model research agents can connect literature retrieval, analysis code, and manuscript preparation, but coherent output does not establish
arXiv:2607.24052v1 Announce Type: new Abstract: High-curvature regions in 3D point clouds encapsulate critical fine-grained geometric semantics yet exhibit a distinct long-tail sparsity in their spati
arXiv:2607.24040v1 Announce Type: new Abstract: Autoregressive decoders emit flat token sequences and cannot enforce hierarchical constraints across output segments, a limitation that becomes acute in
arXiv:2509.11974v3 Announce Type: replace-cross Abstract: Federated Learning (FL) enables collaborative model training among clients without centralising data, making it a widely adopted privacy-enhan
arXiv:2607.22964v1 Announce Type: new Abstract: Tactile gloves digitize contact and force during hand-object interactions, enabling robotics applications in dexterous manipulation, teleoperation, and
arXiv:2607.18263v2 Announce Type: replace Abstract: AI-generated non-consensual intimate imagery (AIG-NCII) is not adequately addressed in AI/ML literature regarding AI-generated media, commonly refer
arXiv:2607.22749v1 Announce Type: cross Abstract: Tracking residual tumor after surgery is essential for catching recurrence early, but automating post-operative glioma segmentation remains a difficul
arXiv:2607.23088v1 Announce Type: cross Abstract: Large Language Models (LLMs) are widely used for code generation, yet their security behavior in realistic development workflows remains underexplored
arXiv:2607.22818v1 Announce Type: cross Abstract: We introduce a new class of fully-quantum Metropolis walks in which both the proposal and acceptance steps are intrinsically quantum. Unlike standard
arXiv:2607.22776v1 Announce Type: new Abstract: Repetitive transcranial magnetic stimulation (rTMS) is a non invasive therapy for Major Depressive Disorder (MDD). In this study, we generate images usi
arXiv:2504.17052v4 Announce Type: replace Abstract: Existing evaluations of political bias in large language models (LLMs) typically classify outputs as left- or right-leaning. We extend this perspect
arXiv:2607.22634v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive (AR) LLMs, generating tokens in parallel. This makes t
arXiv:2607.22963v1 Announce Type: cross Abstract: Synthetic aperture radar (SAR) image generation can mitigate data scarcity, but controllablegeneration under sparse observation angles remains difficu
arXiv:2607.23473v1 Announce Type: new Abstract: Robot policies are typically MLPs mapping observations to actions. Yet robot observations are physical variables, and many action-relevant cues arise no
arXiv:2607.24353v1 Announce Type: new Abstract: Text-to-image generation models can synthesize high-quality images from natural language descriptions, but their performance remains highly sensitive to
arXiv:2407.09013v2 Announce Type: replace Abstract: The attempt to utilize machine learning in PCG has been made in the past. In this survey paper, we investigate how generative artificial intelligenc
arXiv:2607.22724v1 Announce Type: cross Abstract: Group-based policy optimization has been increasingly used to train large language model (LLM) agents from sparse outcome rewards by comparing traject
arXiv:2606.18037v2 Announce Type: replace Abstract: Tool-using LLM agents increasingly use the Model Context Protocol (MCP) to answer from heterogeneous evidence sources, including search, APIs, datab
arXiv:2607.24401v1 Announce Type: cross Abstract: Proxy outcomes (such as short-term behavioral signals, model predictions, or surrogate endpoints) are frequently used in place of primary outcomes tha
arXiv:2607.22648v1 Announce Type: new Abstract: Inspired by the design of client caching in Content Delivery Networks (CDNs), PTStore distributes and replicates popular tensors that form reusable KV c
arXiv:2607.22755v1 Announce Type: cross Abstract: pyALDIC is an open-source Python implementation of augmented Lagrangian digital image correlation (AL-DIC) for full-field displacement and strain meas
arXiv:2607.24583v1 Announce Type: new Abstract: Large scale Bayesian nonparametrics (BNP) learner such as Stochastic Variational Inference (SVI) can handle datasets with large class number and large t
arXiv:2607.22743v1 Announce Type: cross Abstract: Background and Objective: Automatic polyp segmentation supports computer-aided diagnosis and early colorectal cancer detec- tion. Centralized deep lea
arXiv:2607.22549v1 Announce Type: new Abstract: Hybrid quantum-classical protein structure prediction depends strongly on Hamiltonian penalty weights, yet existing lattice-based workflows typically fi
arXiv:2607.19063v2 Announce Type: replace Abstract: Objective Structured Clinical Examinations (OSCEs) are the gold standard for assessing clinical competence, yet scoring remains vulnerable to examin