Contractor Filters
arXiv:2610.18040v1 Announce Type: new Abstract: We introduce Contractor Filters (CFs), a set-membership architecture for nonlinear continuous-time state estimation with bounded uncertainties and spora
Knowledge catalogue
arXiv:2610.18040v1 Announce Type: new Abstract: We introduce Contractor Filters (CFs), a set-membership architecture for nonlinear continuous-time state estimation with bounded uncertainties and spora
arXiv:2610.14025v1 Announce Type: new Abstract: Activation steering controls large language model behavior by adding a direction to hidden activations during inference. For steering to work well, that
arXiv:2610.17098v1 Announce Type: new Abstract: The incorporation of footage from other sources has long been a concern from a copyright perspective, as such usage can harm the interests of rights hol
arXiv:2610.14875v1 Announce Type: new Abstract: While contrastive learning is widely used to learn deterministic representations, it does not inherently provide estimates of uncertainty. Post-hoc unce
arXiv:2603.23356v2 Announce Type: replace-cross Abstract: We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predict
arXiv:2610.14294v1 Announce Type: cross Abstract: Conditional diffusion models can generate high-quality images that align closely with a given prompt. However, samples generated from different random
arXiv:2610.18434v1 Announce Type: cross Abstract: Expected improvement (EI) based on stochastic kriging (SK) surrogate is widely used in continuous simulation optimization, but unknown heteroscedastic
arXiv:2601.18313v2 Announce Type: replace-cross Abstract: This paper proposes a strictly convex chance-constrained stochastic control framework that accounts for uncertainty in control specifications
arXiv:2610.14341v1 Announce Type: new Abstract: We present CoPlanVLM, which uses a Vision Language Model (VLM) to translate a single natural-language instruction and image into coordinated paths for a
arXiv:2610.16737v1 Announce Type: cross Abstract: Video-to-robot pipelines for quadrupedal imitation insert a learned lifting stage, either a monocular depth model or a per-clip 3D reconstruction, to
openai staff are out there turning the office into a stealth game, while my biggest security threat is letting codex, claude code and sumus loose on a test branch without read only permissions enabled
arXiv:2610.18011v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts under a frozen teacher, mitigating the distribution mismatch of off-policy supervision
arXiv:2610.15250v1 Announce Type: new Abstract: Reconstruction-based detectors for multivariate time series anomaly detection typically learn a single entangled representation of normal behavior and f
arXiv:2610.18321v1 Announce Type: new Abstract: Safe autonomous navigation requires not only geometric obstacle avoidance but also semantic awareness. Different object categories demand different safe
arXiv:2610.18446v1 Announce Type: new Abstract: We present CoTL, a framework that learns a compact set of tokens that preserves scene geometry and appearance from unposed multi-view images. Our encode
arXiv:2610.17993v1 Announce Type: new Abstract: Certified machine unlearning ensures the proximity between the unlearned model and a model retrained without the data to be forgotten. Extending this fr
arXiv:2610.14953v1 Announce Type: new Abstract: Contrastive reinforcement learning (CRL) learns goal-conditioned values by associating state--action pairs with the states subsequently reached, assumin
arXiv:2610.16653v1 Announce Type: new Abstract: Counting is a simple task on which transformers can nevertheless fail at long sequence lengths. We study the cost of counting in a single attention laye
arXiv:2610.15012v1 Announce Type: new Abstract: Reliable individual monitoring is essential for dairy cattle welfare and early heat stress detection in Precision Livestock Farming (PLF). However, tran
arXiv:2610.18194v1 Announce Type: new Abstract: Robotic manipulation systems commonly learn object affordances from human-annotated datasets, which reflect interaction possibilities for a human hand r
arXiv:2610.17387v1 Announce Type: new Abstract: Day-ahead (DA) electricity price forecasting is usually posed per market, with a separate model fitted to each grid's own history. This caps accuracy: s
arXiv:2610.14964v1 Announce Type: new Abstract: Cross-material magnetic core loss prediction requires adapting to new material responses with limited measurements. Global feature alignment overlooks d
arXiv:2508.08216v2 Announce Type: replace Abstract: Personalised music-based interventions offer a powerful means of supporting motor rehabilitation by dynamically tailoring auditory stimuli to provid
arXiv:2610.17407v1 Announce Type: new Abstract: Generating realistic time-series requires faithfully reproducing rare but high-impact extreme events. Existing approaches often rely on specialized repr
At AI Engineer New York, OpenAI and Anthropic presented how to give financial agents useful autonomy while keeping consequential decisions under control. The consensus was that safe autonomy depends o
arXiv:2610.14762v1 Announce Type: new Abstract: Model merging combines fine-tuned experts into one network without retraining, and closed-form methods compute each merged layer from statistics of its
arXiv:2610.17532v1 Announce Type: new Abstract: Cross-species portrait animation, which aims to animate a source portrait of species A using a driving video of species B, is particularly challenging d
arXiv:2610.18696v1 Announce Type: new Abstract: Particle picking in cryo-electron microscopy is commonly formulated as an object-detection problem in which individual particles are represented by boun
arXiv:2610.16449v1 Announce Type: cross Abstract: Pseudonymous accounts and complex smart-contract ecosystems substantially hinder the tracing of illicit cryptocurrency fund flows. Existing Graph Neur
Performance on Model Prompt tokens master tok/s pr tok/s Change RTX PRO 6000 Blackwell Qwen3.5-35B-A3B-Q8_0 2048 13,653.58 16,459.56 +20.6% RTX PRO 6000 Blackwell Qwen3.5-35B-A3B-Q8_0 4096 14,090.26 1
arXiv:2610.17114v1 Announce Type: new Abstract: Frontier large language models (LLMs) now reason about space well enough to program robots, yet the world models behind robot policies are implicit, hel
arXiv:2511.12528v5 Announce Type: replace Abstract: Visual Place Recognition (VPR) aims to determine the geographic location of a query image by retrieving its most visually similar counterpart from a
arXiv:2610.16812v1 Announce Type: new Abstract: Symbolic regression (SR) aims to discover interpretable mathematical expressions from data and plays a key role in scientific discovery. However, existi
arXiv:2610.15782v1 Announce Type: new Abstract: Vision-language navigation requires agents to follow natural-language instructions to reach target locations, making high-quality language supervision e
arXiv:2610.18038v1 Announce Type: cross Abstract: World action models (WAMs) built on pretrained video generation models adapt quickly to new robotic tasks, but they forget previously learned tasks un
arXiv:2610.18863v1 Announce Type: cross Abstract: Sampling equilibrium field configurations remains a major computational bottleneck in lattice field theory, motivating the development of generative s
arXiv:2610.15126v1 Announce Type: cross Abstract: Decentralized learning must balance collaboration with personalization across heterogeneous agents. This paper studies when cooperation can support st
arXiv:2610.16867v1 Announce Type: new Abstract: Reliable agentic tool use requires training data that pair diverse multi-step workflows with executable evidence that the requested outcomes were achiev
arXiv:2610.15391v1 Announce Type: new Abstract: Target-conditioned cyclic peptide design requires coordinating interfacial side chains with macrocyclic closure. Existing end-to-end generators concurre
arXiv:2610.16956v1 Announce Type: new Abstract: Historical document analysis is crucial for cultural heritage preservation and low-resource language digitization. However, real historical documents of
arXiv:2610.14333v1 Announce Type: new Abstract: We study decentralized bandit learning in discounted infinite-horizon, general-sum Markov games with continuous actions. Agents observe the public state
arXiv:2610.17083v1 Announce Type: new Abstract: Large Language Models (LLMs) are predominantly trained on imperative programming languages, and existing work on LLM-based robot programming reflects th
arXiv:2610.14388v1 Announce Type: cross Abstract: Neural learners for classification and regression are often criticized as black boxes. We propose a probabilistic decomposition of neural learners tha
arXiv:2610.14605v1 Announce Type: cross Abstract: Current evaluations of multimodal unlearning typically focus on whether a model stops outputting target information. This surface-level criterion, how
arXiv:2510.21974v3 Announce Type: replace Abstract: We introduce Deep Jump Gaussian Processes (DJGP), a novel method for surrogate modeling of a piecewise continuous function on a high-dimensional dom
arXiv:2512.14967v3 Announce Type: replace Abstract: We present a novel numerical method for solving McKean-Vlasov forward-backward stochastic differential equations (MV--FBSDEs) with common noise, com
arXiv:2610.16529v1 Announce Type: new Abstract: Plant fibers are increasingly used as sustainable reinforcements in composites, but the intrinsic variability of their microstructure causes substantial
arXiv:2610.15061v1 Announce Type: new Abstract: Accurate and efficient analysis of dental radiographs has become increasingly important for disease diagnosis and clinical decision making. In particula
arXiv:2610.14385v1 Announce Type: cross Abstract: This article offers an overview of recent developments in deep learning from a control vantage point. It reviews several classes of models including f
arXiv:2610.16269v1 Announce Type: cross Abstract: In astrophysical complex TAIGA there are four Imaging Atmospheric Cherenkov telescopes (IACTs), located at a distance of 300-500 m from each other, du
arXiv:2610.17885v1 Announce Type: new Abstract: Microscopic simulations resolve spatial patterns but are feasible only over small domains and short timescales, whereas bulk descriptions erase those pa
arXiv:2610.15323v1 Announce Type: cross Abstract: Longitudinal health data often exhibit within-subject correlation, subject-specific heterogeneity, and complex nonlinear predictor--response relations
arXiv:2610.16273v1 Announce Type: cross Abstract: Speech timing is fundamental for speech models to recognize words accurately, but how word-timing information is represented in speech models remains
arXiv:2610.16546v1 Announce Type: new Abstract: Basic probabilistic models form the basis of modern deep learning largely by defining the final activation layer of a network and allowing the networks
arXiv:2610.17316v1 Announce Type: cross Abstract: Deep unrolling methods for inverse problems augment traditional reconstruction algorithms with learned priors to improve their performance. These meth
arXiv:2610.17680v1 Announce Type: cross Abstract: Building a co-registered SAR-optical corpus for self-supervised Earth Observation is above all an acquisition problem, yet the main multi-modal datase
arXiv:2610.16597v1 Announce Type: new Abstract: Expressive flow policies can represent multiple high-value actions, but sampling them with few integration steps while retaining tractable action densit
arXiv:2610.14497v1 Announce Type: new Abstract: EEG foundation models (EFMs) have improved EEG representation learning by transferring knowledge from large-scale multi-subject pretraining to downstrea
arXiv:2610.14854v1 Announce Type: new Abstract: Contact-rich manipulation poses a stage-dependent sensory conflict: vision and proprioception are essential for localization and approach, when force is
arXiv:2610.17751v1 Announce Type: cross Abstract: Large language model (LLM)-based multi-agent systems (MAS) are commonly organized around two coordination regimes. Centralized coordination provides e