Knowledge catalogue
arXiv:2412.07151v1 Announce Type: cross Abstract: Distributed model training needs to be adapted to challenges such as the straggler effect and Byzantine attacks. When coordinating the training proces
arXiv:2609.21755v1 Announce Type: new Abstract: Emergency department (ED) decision-making relies on heterogeneous clinical information, including patient history, vital signs, laboratory results, and
arXiv:2603.05807v2 Announce Type: replace Abstract: Event cameras are rapidly rising in popularity for robotic and computer vision tasks because their sparse activation delivers energy-efficient, high
arXiv:2609.21829v1 Announce Type: cross Abstract: Clustering high-dimensional data is a fundamental task in unsupervised machine learning with applications to a variety of domains. In the centralized
Found a great production use case for Jev. I used Jev to organize ~2.3K AI research papers. The total cost was $0.14, and it took about 83 seconds. The process: The papers already had old tags, which
arXiv:2609.21012v1 Announce Type: new Abstract: Artistic style classification is usually studied on complete artworks, where models can exploit global composition, spatial organisation, and iconograph
arXiv:2609.20838v1 Announce Type: new Abstract: In this study, we examine how modern LLMs generate and detect fake news under controlled settings across four manipulation scenarios. These are open-end
arXiv:2609.21948v1 Announce Type: cross Abstract: Learning large-scale vision-language-action (VLA) models from multi-embodiment datasets remains challenging due to heterogeneous action spaces across
arXiv:2609.21293v1 Announce Type: new Abstract: Autonomous software generation (ASG) aims to turn human requirements into executable applications, but delivering these applications does not necessaril
arXiv:2609.21876v1 Announce Type: new Abstract: As an alternative to the additive and extremal biases of average and max pooling, we introduce Geometric Mean Pooling (GMP), a signed pooling operator t
arXiv:2609.21251v1 Announce Type: new Abstract: Gradient-guided diffusion samplers provide flexible priors for inverse problems and conditional generation, but strong guidance can move the sampling tr
arXiv:2609.21576v1 Announce Type: new Abstract: Generating natural co-speech gestures from streaming speech is essential for embodied conversational agents, where motion must be produced while a user
arXiv:2603.24155v3 Announce Type: replace Abstract: Current trajectory prediction models are primarily trained in an open-loop manner, which often leads to covariate shift and compounding errors when
arXiv:2609.21597v1 Announce Type: new Abstract: Monocular 6-DoF pose estimation of non-cooperative targets is important for on-orbit servicing and debris removal. A single-image estimator can confuse
arXiv:2609.21813v1 Announce Type: cross Abstract: In classification-oriented adaptive sensing, posterior samples characterize uncertainty at the current measurement state and can serve two roles: they
arXiv:2609.21303v1 Announce Type: cross Abstract: Product abuse is an individually rare, but growing, problem across the SaaS industry. Highly sophisticated threat actors can misuse security platforms
arXiv:2609.21183v1 Announce Type: cross Abstract: Audio large language models (AudioLLMs) operate reactively, responding only when queried. We introduce proactive audio assistance, where an AudioLLM m
Impressive paper on building recursive self-improving agent harnesses. It's rich with great insights on building effective agent harnesses. If you maintain an agent harness, this paper names three def
arXiv:2609.21454v1 Announce Type: cross Abstract: We revisit Breiman's observation that reducing inter-tree correlation without weakening individual trees can improve random forests. Building on this
arXiv:2609.21938v1 Announce Type: new Abstract: Transformer-based models have recently achieved strong performance on 3D reconstruction from images, and recent works extend them to process video strea
arXiv:2609.21441v1 Announce Type: cross Abstract: Cross-border FM spectrum coordination involves protecting foreign broadcasting services while preserving domestic coverage, amid increasingly large ra
Last week TypeSafe AI unveiled Jev, their first example of a new category of model that they are calling 'System One models' (I'm with Maggie Appleton, I think 'decision models' is a better name for t
arXiv:2609.21381v1 Announce Type: cross Abstract: We investigate whether coupling a time-series foundation model to hydraulic project knowledge improves surrogate forecasting of HEC-RAS water-surface
arXiv:2609.21107v1 Announce Type: new Abstract: While learning from human motions has enabled highly dynamic humanoid skills such as dancing and martial arts in obstacle-free space, traversal through
arXiv:2609.21945v1 Announce Type: new Abstract: Urban transportation networks present complex optimization challenges spanning calibration of high-fidelity simulators and real-time operational control
arXiv:2609.21319v1 Announce Type: new Abstract: Physical control tasks in the natural world, such as driving or object manipulation, frequently exhibit dramatic variations in sensory and compute compl
arXiv:2609.21275v1 Announce Type: new Abstract: We introduce Learned Optimal Inverse Kinematics (LOInK), a method to generate approximately optimal solutions to an inverse kinematics problem. When tra
arXiv:2609.21061v1 Announce Type: new Abstract: Automatic target recognition (ATR) with synthetic aperture sonar (SAS) supports advanced naval capabilities, but deep learning is constrained by scarce
arXiv:2609.21164v1 Announce Type: new Abstract: Integrating diverse data modalities --- such as clinical notes, laboratory results, and medical imaging --- is essential for advancing clinical decision
arXiv:2609.21095v1 Announce Type: new Abstract: We present MarsFM, an image-conditioned latent flow-matching model for local Martian relief estimation from single-band HiRISE RED orthoimagery. The met
The surge in AI development has created unprecedented demand for compute capacity around the globe. This can have negative implications for data processing and pipelines with Apache Spark. Whether you
arXiv:2609.21449v1 Announce Type: new Abstract: World Action Models bring the predictive capabilities of video models into robot action generation, providing a rich foundation for modeling future visu
arXiv:2602.07036v2 Announce Type: replace-cross Abstract: Audio large language models (AudioLLMs) enable instruction following over speech and general audio, but progress is limited by the scarcity of
arXiv:2609.21122v1 Announce Type: new Abstract: Manipulating previously unseen objects remains challenging, as their dynamics depend on latent physical properties, such as friction and mass distributi
arXiv:2609.21573v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves large language models by grounding outputs in external knowledge sources, but this dependency also creat
arXiv:2609.21365v1 Announce Type: new Abstract: Automated needle-loop hooking is a critical step in flexible microelectrode (FME) implantation. This paper presents MicroHookACT, an imitation learning-
arXiv:2609.21280v1 Announce Type: new Abstract: Drug mechanism-of-action (MoA) modeling commonly relies on perturbational transcriptomes, but matched microRNA (miRNA) measurements are often unavailabl
arXiv:2609.21811v1 Announce Type: new Abstract: Multimodal survival models can combine complementary prognostic information from whole-slide images and genomic profiles, but effective fusion remains c
arXiv:2609.20997v1 Announce Type: new Abstract: Symbolic regression aims to recover closed-form equations from observations, providing interpretable models for scientific discovery. Existing approache
arXiv:2609.21241v1 Announce Type: new Abstract: Producing accurate annotations for deep learning based image segmentation is both costly and labor intensive. This challenge is especially evident in wi
arXiv:2609.21967v1 Announce Type: cross Abstract: We introduce NemotronLabs VoiceChat, an open full-duplex speech-to-speech model with native tool-calling capabilities. NemotronLabs VoiceChat combines
arXiv:2609.21870v1 Announce Type: cross Abstract: Modern deep learning models achieve impressive generalization through over-parameterization, but this paradigm often struggles with overfitting and me
Nice paper showing a better way to evolve agent skills. And they achieve 40–70% less token cost compared to frontier evolving methods. The idea is to let agents improve their skill prompts by ranking
arXiv:2609.21114v1 Announce Type: new Abstract: Robots carrying out tasks in dark environments need to localize from a single RGB camera, in light so low that the per-pixel signal approaches the senso
arXiv:2609.21822v1 Announce Type: new Abstract: While object detection has advanced through improved architectures and open-vocabulary models, we provide strong evidence that benchmark quality is limi
arXiv:2609.21626v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed for enterprise information extraction (IE), where the same document must be reorganized different
arXiv:2609.21199v1 Announce Type: new Abstract: Manga is a comic drawn by black and white paints gaining popularity around the world. Onomatopoeia in Manga specifically appeals to the audience with it
arXiv:2609.21789v1 Announce Type: new Abstract: Most multilingual dysarthria-severity systems either train on a single aetiology-language pair or pool heterogeneous aetiologies into one label space. W
arXiv:2609.21590v1 Announce Type: cross Abstract: Accurate prediction of unsteady aerodynamic loads remains a major challenge in turbomachinery design. High-fidelity Computational Fluid Dynamics (CFD)
arXiv:2609.21059v1 Announce Type: cross Abstract: Plant growth and agricultural production form the foundation of a country's sustainable development and directly impact human livelihoods. Recent adva
arXiv:2609.21493v1 Announce Type: new Abstract: Multimodal large language models, or MLLMs, perform well at visual understanding and structured generation, yet these capabilities do not establish whet
arXiv:2609.22056v1 Announce Type: cross Abstract: Multi-hop retrieval failures are not uniformly distributed across queries: they cluster in structurally predictable subpopulations. We prove two resul
arXiv:2609.21583v1 Announce Type: cross Abstract: Feedforward Spiking Neural Networks (SNNs) typically propagate every generated spike indiscriminately, disregarding whether the information is redunda
arXiv:2609.22040v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models for autonomous driving operate primarily through feedforward inference across the perception--reasoning--pla
arXiv:2609.21351v1 Announce Type: new Abstract: Table extraction suffers from frequent structural errors and semantic hallucinations. We propose PrismAlign, a multi-VLM framework aligning diverse visu
arXiv:2609.21005v1 Announce Type: new Abstract: The rapid proliferation of unauthorized unmanned aerial vehicles (UAVs) has created a growing need for robust, jamming-resistant counter-UAV systems for
arXiv:2609.21369v1 Announce Type: cross Abstract: This paper presents a comprehensive framework for robot manipulation failure analysis that includes binary failure detection, failure categorization,
arXiv:2609.21753v1 Announce Type: new Abstract: Contact-rich manipulation requires policies to generate precise actions by reasoning over contact forces, robot configurations, and interaction historie
arXiv:2609.21541v1 Announce Type: new Abstract: Multi-label few-shot learning (MLFSL) remains a significant challenge in medical image analysis (MIA). Current metric-based meta-learning methods face t
arXiv:2609.20971v1 Announce Type: new Abstract: Long-context large language model inference is increasingly limited by prefill, where dense self-attention processes the entire prompt before generation