Knowledge catalogue
arXiv:2609.25067v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has become an effective approach for learning visual representations without manual annotations. Among SSL approaches,
arXiv:2511.02769v2 Announce Type: replace Abstract: Many molecular Transformers lack probabilistic latent variables for posterior inference and latent interpolation. We introduce STAR-VAE, a SELFIES-e
NVIDIA Cluster Readiness Engine (NVCRE) is an open‑source Kubernetes controller that runs real distributed workloads across topology‑aware node groups to certify GPU cluster readiness before productio
arXiv:2609.22836v1 Announce Type: new Abstract: Time series foundation models (TSFMs) have recently delivered impressive zero-shot performance across diverse forecasting tasks. However, real-world dec
arXiv:2603.11984v2 Announce Type: replace Abstract: Diffusion-based visuomotor policies model complex action distributions through iterative denoising, but repeated inference adds latency to robotic c
arXiv:2503.03370v3 Announce Type: replace Abstract: Cross-domain cell detection for microscopic images suffers from performance degradation due to distribution shifts across imaging domains. Unsupervi
arXiv:2609.22332v1 Announce Type: cross Abstract: Generalizable robot manipulation requires predicting how a scene will evolve, identifying where interactions are feasible, and determining how to act.
arXiv:2609.24312v1 Announce Type: new Abstract: Analog video transmission (VTX) remains widespread in FPV drones due to low latency, weight and low cost. However analog VTX suffers from complex spatia
arXiv:2609.23578v1 Announce Type: new Abstract: As AI agents become increasingly capable, agent-driven robotic control is emerging as a compelling paradigm. However, prevailing vision-language-action
arXiv:2609.23146v1 Announce Type: new Abstract: Non-intrusive load monitoring (NILM) estimates appliance-level consumption from a whole-home meter, but appliance-specific models and fixed output inven
arXiv:2609.22141v1 Announce Type: cross Abstract: Automated seizure detection from scalp electroencephalography (EEG) is difficult because seizure morphology varies among patients and seizure samples
arXiv:2609.23979v1 Announce Type: cross Abstract: Attention encoder-decoder (AED) Speech Foundation Models achieve strong ASR performance but can generate acoustically unsupported text when inputs con
arXiv:2609.23717v1 Announce Type: new Abstract: Global vision--language similarities compress an image and a caption into one vector, preserving semantics but not which word corresponds to which regio
arXiv:2609.23352v1 Announce Type: new Abstract: Bimanual interaction produces complementary tactile views of the same physical process, yet existing tactile representation learning largely models the
arXiv:2609.22282v1 Announce Type: new Abstract: Reconstructing visual stimuli from electroencephalography (EEG) is difficult because scalp measurements have high temporal but limited spatial resolutio
arXiv:2609.22866v1 Announce Type: new Abstract: We introduce Causilo, a tabular foundation model (TFM) that combines frontier predictive performance with exceptionally fast inference. On TabArena, Cau
arXiv:2609.22274v1 Announce Type: new Abstract: Recent advances in humanoid robotics have produced diverse skills through reinforcement learning, motion imitation, and generative modeling. Yet these c
arXiv:2609.23178v1 Announce Type: new Abstract: Language models are appealing tools for research on the past. But to trust the evidence a model provides, researchers need to know whether its responses
arXiv:2609.22734v1 Announce Type: new Abstract: Clinical domain classification plays an important role in organizing and analyzing large volumes of unstructured medical text. However, medical transcri
arXiv:2504.14280v2 Announce Type: replace Abstract: As machine learning evolves, domain generalization (DG) and domain adaptation (DA) have become crucial for improving model robustness across diverse
arXiv:2609.23961v1 Announce Type: new Abstract: Monocular colonoscopic 3D reconstruction is important for surgical robotic colonoscopy, but remains challenging due to weak texture, specular reflection
arXiv:2609.22536v1 Announce Type: new Abstract: Bangla, the seventh most spoken language in the world, exhibits significant regional dialectal diversity, with dialects such as Barishal, Chattogram, Sy
arXiv:2609.23012v1 Announce Type: new Abstract: Generative vision-language models (VLMs) offer a counting paradigm in which one model produces both a count and a natural-language account of the scene,
arXiv:2609.24791v1 Announce Type: cross Abstract: Challenging behaviors including aggression, self-injury, and property destruction are observed in 68% of autistic youth and pose risks to youth and ca
arXiv:2609.24410v1 Announce Type: new Abstract: Speech-to-text engines are extremely needed nowadays for different applications, representing an essential enabler in human-robot interaction. Still, so
arXiv:2609.23397v1 Announce Type: new Abstract: Shrimp diseases continue to cause devastating losses in the aquaculture industry, driving a critical need for robust, automated detection. This work con
arXiv:2609.24180v1 Announce Type: new Abstract: Visual grasp proposal generation has advanced rapidly, yet converting a selected proposal into a stable physical grasp remains a central execution-stage
arXiv:2609.23418v1 Announce Type: new Abstract: Language-guided manipulation can depend on physical properties that visible appearance does not reveal. Temperature is one such property, but object dat
arXiv:2609.22611v1 Announce Type: new Abstract: Humanoid robots can acquire complex skills by imitating kinematic humanoid motion references, yet reliable references for contact-rich interactions rema
arXiv:2609.23376v1 Announce Type: cross Abstract: Open-vocabulary audio-visual event localization (OV-AVEL) grounds a text-queried event in time from video, audio, and language. The supervision source
arXiv:2609.22521v1 Announce Type: new Abstract: The performance of learned robot visuomotor policies depends heavily on the size and quality of their training data, yet collecting high-quality demonst
arXiv:2609.24386v1 Announce Type: new Abstract: Childhood stunting remains a major public health concern in Bangladesh and reflects long-term growth failure influenced by child, maternal, household, s
arXiv:2609.22379v1 Announce Type: new Abstract: High-resolution orbital imagery offers a rich record of the Martian surface, but sparse geological labels limit supervised representation learning. We p
arXiv:2609.23935v1 Announce Type: new Abstract: Post-training turns a general next-token predictor into a chat model with a persistent assistant persona. If that persona is a character the model plays
arXiv:2609.24736v1 Announce Type: new Abstract: Mitotic figure (MF) analysis supports tumor grading and prognostic assessment, but automated models remain sensitive to differences in tissue type and i
arXiv:2609.23950v1 Announce Type: cross Abstract: Cardiovascular magnetic resonance (CMR) provides comprehensive cardiac assessment but remains underutilized because of the complexity of acquisition,
arXiv:2609.22687v1 Announce Type: new Abstract: We present PanoSeg3R, a feed-forward framework for 3D panoramic semantic segmentation. Unlike existing methods designed for perspective inputs, PanoSeg3
arXiv:2609.24919v1 Announce Type: new Abstract: Recent advances in pixel-space diffusion models have narrowed the image quality gap with latent-space diffusion, but still converge more slowly and lag
arXiv:2609.24422v1 Announce Type: new Abstract: Hierarchical data is ubiquitous in the empirical sciences and is most commonly analyzed with generalized linear mixed-effects models (GLMMs). Bayesian i
arXiv:2609.23139v1 Announce Type: new Abstract: Most medical vision-language models (VLMs) excel at open-ended report generation and VQA but provide limited support for structured, fine-grained clinic
arXiv:2609.23325v1 Announce Type: new Abstract: Single-cell foundation models (scGPT, scBERT, Geneformer) achieve cell-type classification accuracy up to 97.5% in our experiments, yet this aggregate a
arXiv:2609.22506v1 Announce Type: new Abstract: Vision Transformers allocate most parameters to multi-layer perceptrons (MLPs) for channel mixing, while token interactions usually rely on quadratic mu
arXiv:2607.11498v2 Announce Type: replace Abstract: Vision-language-action (VLA) models require 3D spatial reasoning, yet RGB observations encode robot-object geometry only implicitly. Lifting depth w
arXiv:2609.23019v1 Announce Type: cross Abstract: Soma instance segmentation, i.e., identifying and delineating individual cell somas as distinct instances, is crucial for cellular analysis and connec
arXiv:2510.03095v4 Announce Type: replace Abstract: Diffusion- and flow-based generative models have recently demonstrated strong performance in protein backbone generation tasks, offering unprecedent
arXiv:2609.23223v1 Announce Type: cross Abstract: Day-ahead electricity price forecasts support trading and storage decisions, but for battery arbitrage predicting intraday price spreads is more relev
arXiv:2609.24559v1 Announce Type: new Abstract: We present t_0, a family of open-weights foundation models for forecasting with multivariate context. We release its first two members: exttt{t0-alpha}
arXiv:2609.23580v1 Announce Type: new Abstract: Reactive vision--language--action (VLA) models struggle with long-horizon manipulation when visually similar observations can correspond to different ac
arXiv:2609.24136v1 Announce Type: new Abstract: Brain-to-image retrieval seeks to identify the visual stimulus that elicited a non-invasive neural response. Candidate images are typically represented
arXiv:2609.23758v1 Announce Type: new Abstract: Few-shot recognition with frozen visual features is especially fragile under domain shift and one-shot supervision, where a single labelled image is an
arXiv:2609.23919v1 Announce Type: cross Abstract: Automated brain tumor segmentation supports diagnosis, treatment planning, and monitoring of disease progression, but building models that generalize
arXiv:2609.24274v1 Announce Type: new Abstract: Deploying language-conditioned manipulation without a dedicated GPU requires efficient inference and action chunks that cover the delay between policy q
arXiv:2607.18840v2 Announce Type: replace Abstract: World Action Models (WAMs) offer a promising paradigm for robotic manipulation by jointly modeling visual state transitions and robot actions. Howev
arXiv:2609.22631v1 Announce Type: new Abstract: Accurate automated interpretation of electrocardio- grams (ECGs) is essential for early detection of cardiac condi- tions such as myocardial infarction
arXiv:2609.21176v1 Announce Type: new Abstract: This paper addresses the challenges of dynamic scene synthesis from sparse-view videos. Existing methods employ geometric priors, adaptive optimization,
arXiv:2609.21792v1 Announce Type: new Abstract: Navigating toward human callers is an important capability for rescue robots operating where visual contact is degraded or occluded. We present Acoustic
arXiv:2609.21743v1 Announce Type: cross Abstract: Entropy minimization is a standard objective for test-time adaptation (TTA), but it can fail in imbalanced binary segmentation. Unlike image classific
arXiv:2609.21763v1 Announce Type: new Abstract: A medical model's benchmark score does not establish that the same conclusion holds under a different evaluation. This study tests whether claims about
arXiv:2609.20904v1 Announce Type: cross Abstract: Hybrid motor-imagery brain-computer interfaces (MI-BCIs) combining EEG and fNIRS can outperform EEG-only systems by exploiting complementary electroph
arXiv:2609.21887v1 Announce Type: new Abstract: The gold standard datasets for mapping connectomes are electron microscopy volumes of densely labeled neural tissue at nanometer resolution. Yet reconst