Knowledge catalogue
arXiv:2610.16264v1 Announce Type: new Abstract: Electroencephalography (EEG) is a non-invasive, scalable source of quantitative biomarkers for the early diagnosis of brain disorders, and deep represen
arXiv:2610.16680v1 Announce Type: cross Abstract: Resampling is the standard remedy against weight degeneracy in particle filters, yet its effect on the spectrum of the particle second-moment matrix i
arXiv:2610.16533v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is reshaping how large language models (LLMs) acquire reasoning capabilities, yet the optimizers
arXiv:2302.00985v3 Announce Type: replace-cross Abstract: We consider online scheduling on unrelated (heterogeneous) machines in a speed-oblivious setting, where an algorithm is unaware of the exact j
arXiv:2610.15745v1 Announce Type: new Abstract: Multimodal 3D occupancy prediction underpins safe autonomous driving through comprehensive scene understanding. However, existing methods have largely p
arXiv:2601.15431v2 Announce Type: replace-cross Abstract: Radiance field-based rendering methods have attracted significant interest from the computer vision and computer graphics communities. They en
arXiv:2610.17029v1 Announce Type: new Abstract: Neural operator splitting composes a library of neural operators, one per physical mechanism, into zero-shot simulators of new equations. Existing appro
arXiv:2610.13996v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards improves mathematical reasoning when a final answer can be checked, but a correct answer does not certify
arXiv:2610.15458v1 Announce Type: new Abstract: Existing analyses of interval length in split conformal prediction largely focus on clean data. However, how contamination at the training and calibrati
arXiv:2610.14405v1 Announce Type: cross Abstract: Reinforcement learning (RL) has driven substantial progress in coding agents by relying on verified successful trajectories as learning signals. Howev
arXiv:2602.11049v2 Announce Type: replace Abstract: Ensuring safe robot operation in cluttered and dynamic environments remains a fundamental challenge. While control barrier functions (CBFs) provide
Square is launching new hardware: a big kiosk for ordering things that has a touchscreen and lets you talk to an AI. It's called the Square Kiosk. Square says the Kiosk, which has a large pill shape,
arXiv:2610.15604v1 Announce Type: new Abstract: Traffic sign detection plays a vital role in intelligent transportation systems, supporting the safe operation of advanced driver assistance systems and
arXiv:2610.17323v1 Announce Type: new Abstract: Face recognition systems are deployed widely enough that a photograph shared online can be matched without its subject's consent. Generator-based protec
arXiv:2610.18645v1 Announce Type: new Abstract: Video prediction requires models to capture complex spatiotemporal dependencies and to retain relevant information over long sequences. PredRNN and its
arXiv:2610.17904v1 Announce Type: new Abstract: Continual learning (CL) adapts pretrained models to a sequence of tasks while retaining knowledge acquired from earlier tasks. When task data are sensit
arXiv:2606.19774v2 Announce Type: replace Abstract: Action chunking enables robot policies to produce temporally coherent behavior, but generating multi-step action sequences with flow-based policies
Startups are built on relationships. That’s why IRL events are a core part of our growth strategy at @lemma_ . We hosted our biggest one yet during @SFTechWeek : The Agent Economy Gala. 400+ founders,
arXiv:2610.14601v1 Announce Type: new Abstract: In this work, we aim to develop an embodied MLLM agent that understands and solves embodied tasks by learning, abstracting, and reusing transferrable an
arXiv:2610.16816v1 Announce Type: cross Abstract: Global reanalyses are too coarse to resolve the convective systems that produce most West African monsoon rainfall. In this work, we use U-Net based a
arXiv:2610.18811v1 Announce Type: new Abstract: In this work, we study grokking in a simple, analytically tractable setting whose rich phenomenology allows us to disentangle the effects of initializat
arXiv:2610.18495v1 Announce Type: cross Abstract: In order to execute quantum algorithms on bosonic quantum computers, it is necessary to encode their inputs into a desired target quantum state, with
arXiv:2610.18711v1 Announce Type: new Abstract: Current recipes for robot learning require massive amounts of robot demonstrations to obtain robust and adaptive policies. In this work, we introduce St
arXiv:2610.17925v1 Announce Type: new Abstract: Decisions that weigh several reward signals against each other require the joint distribution of the return vector. Categorical critics scale exponentia
arXiv:2610.15560v1 Announce Type: new Abstract: Existing navigation systems commonly rely on dedicated depth sensors or explicit depth reconstruction, while learning to generate trajectories directly
arXiv:2610.15341v1 Announce Type: new Abstract: The inherent variability of fMRI responses across trials encourages a generative view of the stimulus-to-response mapping. Prior generative encoders oft
arXiv:2510.17503v2 Announce Type: replace Abstract: We study the online stochastic difference-of-convex (DC) program min_{x in R^n} F(x) = G(x) - H(x) + r_1(x) - r_2(x), which covers sparse learning w
As strata is somewhat new, I assume that some people din't yet learn how to finetune it for best performance on their machine. I find documentation a bit hard to navigate (use your agents for this!),
arXiv:2610.15585v1 Announce Type: new Abstract: World Action Models (WAMs), often built upon pretrained video-generation world models, have emerged as a promising framework for general-purpose and ope
arXiv:2509.23097v4 Announce Type: replace Abstract: Foundation models (FM) have transformed computational pathology but remain computationally prohibitive for clinical deployment due to their massive
arXiv:2610.14338v1 Announce Type: cross Abstract: TREGO, a trust-region Bayesian optimization (BO) method for expensive blackbox problems, has convergence guarantees, but only for exact function value
arXiv:2610.14567v1 Announce Type: cross Abstract: This paper develops strong Gaussian approximations (KMT type) for constant learning rate stochastic gradient descent (SGD). We work with heavy tailed
arXiv:2603.28916v2 Announce Type: replace Abstract: Football action-value approaches estimate scoring, possession, or other downstream outcome value; complementary descriptions can characterise how a
arXiv:2610.17483v1 Announce Type: new Abstract: Machine learning surrogates of partial differential equations (PDEs) are commonly trained on data generated by numerical solvers. Therefore, the trainin
arXiv:2610.15512v1 Announce Type: new Abstract: Coherent multi-shot audio-visual video generation requires maintaining consistent identities while depicting evolving states and coordinating sounds acr
arXiv:2610.16451v1 Announce Type: new Abstract: Fine-tuning large language models at scale is increasingly limited by the memory cost of backpropagation. Zeroth-Order (ZO) optimizers reduce this burde
arXiv:2503.07775v3 Announce Type: replace Abstract: Resource-efficiently computing representations of probability distributions and the distances between them while only having access to the samples i
arXiv:2610.14682v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) agents are typically evaluated by whether they reach a target and how efficiently they follow an instructed route,
arXiv:2610.15322v1 Announce Type: cross Abstract: Enabling the reuse and composition of knowledge and capabilities distributed across foundation models is an important step toward building scalable ar
AI factory deployment has long been a race to secure graphics processing units, but the builders of those systems are finding that compute is only half the problem. Data pipelines, storage costs and t
arXiv:2603.06280v2 Announce Type: replace Abstract: Long-horizon mobile manipulation needs whole-body demonstrations, and collecting them is the bottleneck. Keeping the robot in the loop ties the data
arXiv:2610.18005v1 Announce Type: new Abstract: Surface reconstruction from range scans is challenging in the presence of noise and outliers, as fidelity to observations must be balanced against sensi
arXiv:2610.15645v1 Announce Type: new Abstract: Surgical world models must turn prospective robot actions into visually faithful, structurally consistent instrument motion. We introduce SurgCast, whic
arXiv:2610.15766v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) and vision--language--action models have provided robots with new capabilities for long-horizon task und
arXiv:2610.15095v1 Announce Type: new Abstract: LLM multi-agent systems split work across agents that communicate through text. An agent summarizes its findings, another agent receives the text. This
arXiv:2610.17692v1 Announce Type: new Abstract: 3D scene graph prediction is commonly optimized with object-node and relation-edge classification losses. These objectives encourage exact object and re
arXiv:2610.16338v1 Announce Type: new Abstract: Recent years have witnessed rapid progress in joint audio--visual generation. However, audio--visual synchronization remains a challenge, as generated s
arXiv:2610.18110v1 Announce Type: cross Abstract: Multimodal medical data captures complementary aspects of disease. It provides a comprehensive basis for diagnosis and the identification of biologica
arXiv:2610.16990v1 Announce Type: new Abstract: Tabular data generation aims to synthesize realistic samples from limited observations while faithfully capturing the underlying data distribution. Tabu
arXiv:2610.17448v1 Announce Type: new Abstract: Gaps, skips, and mistakes are the normal state of a historical register: rows go missing, tables cross page breaks, columns slip under wrong names, and
arXiv:2610.15699v1 Announce Type: new Abstract: Generative modeling for tabular data has advanced to the point where models can synthesize realistic records, recover missing values, and generate sampl
arXiv:2610.17540v1 Announce Type: cross Abstract: Textual reasoning before acting has improved vision-language-action (VLA) models, but at the cost of latency: every action conditioned on the reasonin
arXiv:2610.17574v1 Announce Type: new Abstract: Tracking object motion within a gripper provides essential feedback for robotic manipulation. However, limited contact coverage and uneven deformation m
arXiv:2610.14651v1 Announce Type: new Abstract: The recent Segment Anything Model 3 (SAM3) extends powerful promptable segmentation from spatial cues to concepts, raising the prospect of a single foun
arXiv:2610.14626v1 Announce Type: new Abstract: Mixed-variable optimization in scientific discovery often requires exploring large combinatorial spaces under costly experimental evaluations, making sa
Hellow fellow AI-generated goblins of r/StableDiffusion For a few weeks I’ve been stress-testing my tool, Arthemy Krea-2 Tuner: https://github.com/aledelpho/comfyui-arthemy-krea2-tuner I wanted to inv
arXiv:2610.16429v1 Announce Type: cross Abstract: We consider inverse problems regularized by a trained neural network with convex activations and unrestricted weights. The resulting optimization prob
arXiv:2610.17588v1 Announce Type: new Abstract: Muon controls weight updates through the RMS movement of a linear layer's output. This implicitly treats the linear output as a proxy for the full modul
arXiv:2610.17596v1 Announce Type: new Abstract: Vision-language models are increasingly used to identify and describe places, yet their recognition and knowledge of specific cultures remain poorly und
arXiv:2610.14440v1 Announce Type: new Abstract: Asynchronous reinforcement-learning post-training of large language models is computationally efficient but inherently off-policy: the learner updates o